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3DLinker - An E(3) Equivariant Variational Autoencoder | 2,022 | ICML | Oral | 4 | null | 3 | Yes | null | 45,879 | 19 | Molecular Linker Design;E(3) Equivariant Graph Variational Autoencoder;Conditional Generative Models;3D Molecular Structure Prediction | https://arxiv.org/pdf/2205.07309 | https://icml.cc/media/icml-2022/Slides/18143.pdf |
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness | 2,022 | ICML | Oral | 4 | null | 3 | Yes | null | 44,347 | 47 | Counterfactual Inference;Data Integration;Fair Representation Learning;Batch Effect Correction | https://arxiv.org/pdf/2106.08161 | https://icml.cc/media/icml-2022/Slides/17234.pdf |
Correct-N-Contrast - A Contrastive Approach for Improving Robustness to Spurious Correlations | 2,022 | ICML | Oral | 7 | null | 4 | Yes | null | 44,964 | 78 | Robust Machine Learning;Spurious Correlations;Contrastive Learning;Representation Alignment | https://arxiv.org/pdf/2203.01517 | https://icml.cc/media/icml-2022/Slides/18224_Wlco9OF.pdf |
Learning inverse folding from millions of predicted structures | 2,022 | ICML | Oral | 7 | null | 3 | Yes | null | 42,125 | 18 | Inverse Folding Prediction;Protein Structure Prediction;Generative Models for Protein Design;Sequence-to-Sequence Learning in Protein Engineering | https://proceedings.mlr.press/v162/hsu22a/hsu22a.pdf | https://icml.cc/media/icml-2022/Slides/16886.pdf |
Monarch - Expressive Structured Matrices for Efficient and Accurate Training | 2,022 | ICML | Oral | 5 | null | 8 | Yes | null | 43,885 | 44 | Structured Matrices;Sparse Training;Efficient Neural Network Training;Matrix Approximation Techniques | https://arxiv.org/pdf/2204.00595 | https://icml.cc/media/icml-2022/Slides/17900_R7TNeV4.pdf |
POEM - Out-of-Distribution Detection with Posterior Sampling | 2,022 | ICML | Oral | 3 | null | 3 | Yes | null | 54,444 | 34 | Out-of-Distribution Detection;Posterior Sampling;Outlier Detection;Neural Network Regularization | https://arxiv.org/pdf/2206.13687 | https://icml.cc/media/icml-2022/Slides/16652.pdf |
Path-Gradient Estimators for Continuous Normalizing Flows | 2,022 | ICML | Oral | 5 | null | 3 | Yes | null | 39,565 | 29 | Path-Gradient Estimators;Continuous Normalizing Flows;Variational Inference;High-Dimensional Systems | https://arxiv.org/pdf/2206.09016 | https://icml.cc/media/icml-2022/Slides/17304_0S8DqlX.pdf |
Privacy for Free - How does Dataset Condensation Help Privacy | 2,022 | ICML | Oral | 8 | null | 3 | Yes | null | 53,800 | 24 | Dataset Condensation;Differential Privacy;Membership Inference Attacks;Data Privacy in Machine Learning | https://arxiv.org/pdf/2206.00240 | https://icml.cc/media/icml-2022/Slides/18236.pdf |
Rethinking Image-Scaling Attacks | 2,022 | ICML | Oral | 9 | null | 4 | Yes | null | 47,649 | 44 | Image Scaling Algorithms;Adversarial Attacks;Machine Learning Vulnerabilities;Decision-Based Black-Box Attacks | https://arxiv.org/pdf/2104.08690 | https://icml.cc/media/icml-2022/Slides/16968_QVuMEKF.pdf |
RieszNet and ForestRiesz - Automatic Debiased | 2,022 | ICML | Oral | 3 | null | 4 | Yes | null | 46,414 | 33 | Automatic Debiasing;Riesz Representation;Neural Networks;Random Forests | https://arxiv.org/pdf/2110.03031 | https://icml.cc/media/icml-2022/Slides/16312_f0zLRYT.pdf |
To Smooth or Not When Label Smoothing Meets Noisy Labels | 2,022 | ICML | Oral | 5 | null | 6 | Yes | null | 46,876 | 27 | Label Smoothing;Noisy Label Learning;Regularization Techniques;Negative Label Smoothing | https://arxiv.org/pdf/2106.04149 | https://icml.cc/media/icml-2022/Slides/17074.pdf |
Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning | 2,022 | ICML | Oral | 8 | null | 4 | No | null | 51,214 | 20 | Topology-Aware Network Pruning;Graph Neural Networks;Reinforcement Learning;Model Compression | https://arxiv.org/pdf/2102.03214 | https://icml.cc/media/icml-2022/Slides/16772.pdf |
Understanding Dataset Difficulty with V-Usable Information | 2,022 | ICML | Oral | 9 | null | 4 | Yes | null | 58,804 | 32 | Dataset Difficulty Estimation;V-Usable Information;Pointwise V-Information;NLP Benchmark Analysis | https://arxiv.org/pdf/2110.08420 | https://icml.cc/media/icml-2022/Slides/16634.pdf |
Unified Scaling Laws for Routed Language Models | 2,022 | ICML | Oral | 13 | null | 6 | Yes | null | 45,020 | 84 | Scaling Laws in Language Models;Routing Networks;Neural Network Architecture Evaluation;Effective Parameter Count | https://arxiv.org/pdf/2202.01169 | https://icml.cc/media/icml-2022/Slides/17820.pdf |
data2vec - A General Framework for Self-supervised Learning in Speech, Vision and Language | 2,022 | ICML | Oral | 3 | null | 6 | Yes | null | 47,928 | 14 | Self-supervised Learning;Multimodal Learning;Contextualized Representations;Speech Recognition | https://arxiv.org/pdf/2202.03555 | https://icml.cc/media/icml-2022/Slides/16644.pdf |
Adversarial Example Does Good - Preventing Painting Imitation from | 2,023 | ICML | Oral | 5 | null | 4 | Yes | null | 43,771 | 12 | Adversarial Training;Diffusion Models;Copyright Protection in AI Art;Image Synthesis | https://arxiv.org/pdf/2302.04578 | https://icml.cc/media/icml-2023/Slides/25469.pdf |
Audio Pre-Training with Acoustic Tokenizers | 2,023 | ICML | Oral | 4 | null | 3 | Yes | null | 49,406 | 28 | Self-Supervised Learning for Audio;Acoustic Tokenization;Audio Representation Learning;Audio Classification Benchmarking | https://arxiv.org/pdf/2212.09058 | https://icml.cc/media/icml-2023/Slides/25555.pdf |
Bidirectional Adaptation for Robust Semi-Supervised Learning | 2,023 | ICML | Oral | 3 | null | 3 | Yes | null | 52,501 | 8 | Robust Semi-Supervised Learning;Distribution Adaptation;Debiased Pseudo-Labeling;Theoretical Framework for SSL | https://proceedings.mlr.press/v202/jia23a/jia23a.pdf | https://icml.cc/media/icml-2023/Slides/25533.pdf |
Evaluating Self-Supervised Learning via Risk Decomposition | 2,023 | ICML | Oral | 13 | null | 4 | Yes | null | 58,816 | 28 | Self-Supervised Learning;Risk Decomposition;Error Analysis in Representation Learning;Evaluation Metrics for SSL Models | https://arxiv.org/pdf/2302.03068 | https://icml.cc/media/icml-2023/Slides/25480_fMGoWdI.pdf |
Fast Inference from Transformers via Speculative Decoding | 2,023 | ICML | Oral | 5 | null | 3 | Yes | null | 34,452 | 14 | Speculative Decoding;Parallel Inference;Autoregressive Models | https://arxiv.org/pdf/2211.17192 | https://icml.cc/media/icml-2023/Slides/25546_yAOj5U8.pdf |
Instant Soup - Cheap Pruning Ensembles in A Single Pass Can | 2,023 | ICML | Oral | 3 | null | 7 | Yes | null | 46,357 | 8 | Pruning Ensembles;Lottery Ticket Hypothesis;Model Fine-Tuning;Large Pre-trained Transformers | https://arxiv.org/pdf/2306.10460 | https://icml.cc/media/icml-2023/Slides/25544.pdf |
ODS - Test-Time Adaptation in the Presence of Open-World Data Shift | 2,023 | ICML | Oral | 7 | null | 7 | Yes | null | 43,543 | 21 | Test-Time Adaptation;Open-World Data Shift;Covariate and Label Distribution Shift | https://proceedings.mlr.press/v202/zhou23e/zhou23e.pdf | https://icml.cc/media/icml-2023/Slides/25549.pdf |
Pre-training for Speech Translation - CTC Meets Optimal Transport | 2,023 | ICML | Oral | 5 | null | 10 | Yes | null | 48,994 | 21 | Speech-to-Text Translation;Connectionist Temporal Classification;Optimal Transport;Siamese Neural Networks | https://arxiv.org/pdf/2301.11716 | https://icml.cc/media/icml-2023/Slides/25497.pdf |
Refining Generative Process with Discriminator Guidance | 2,023 | ICML | Oral | 15 | null | 8 | Yes | null | 45,867 | 19 | Score-based Diffusion Models;Discriminator-guided Learning;Generative Adversarial Networks (GANs) Alternative Approaches;Image Generation Techniques | https://arxiv.org/pdf/2211.17091 | https://icml.cc/media/icml-2023/Slides/25468.pdf |
Subequivariant Graph Reinforcement Learning in 3D Environments | 2,023 | ICML | Oral | 8 | null | 5 | Yes | null | 47,869 | 21 | Morphology-Agnostic Reinforcement Learning;Subequivariant Graph Neural Networks;3D Environment Exploration;Policy Optimization via Geometric Symmetry | https://arxiv.org/pdf/2305.18951 | https://icml.cc/media/icml-2023/Slides/25559.pdf |
Which Features are Learnt by Contrastive Learning | 2,023 | ICML | Oral | 6 | null | 5 | Yes | null | 54,697 | 62 | Contrastive Learning;Representation Learning;Feature Suppression;Class Collapse | https://arxiv.org/pdf/2305.16536 | https://icml.cc/media/icml-2023/Slides/25437_64AmEtv.pdf |
Causal normalizing flows - from theory to practice | 2,023 | NeurIPS | Oral | 5 | null | 3 | Yes | null | 52,327 | 67 | Causal Inference;Normalizing Flows;Autoregressive Models;Counterfactual Reasoning | https://arxiv.org/pdf/2306.05415 | https://neurips.cc/media/neurips-2023/Slides/73851.pdf |
Conformal Meta-learners for Predictive Inference of | 2,023 | NeurIPS | Oral | 5 | null | 3 | Yes | null | 53,153 | 25 | Individual Treatment Effects;Conformal Prediction;Meta-Learning;Causal Inference | https://arxiv.org/pdf/2308.14895 | https://neurips.cc/media/neurips-2023/Slides/72090.pdf |
Learning Linear Causal Representations from Interventions | 2,023 | NeurIPS | Oral | 3 | null | 3 | Yes | null | 62,186 | 31 | Causal Inference;Identification of Latent Variables;Contrastive Learning;High-Dimensional Geometry in Causal Learning | https://arxiv.org/pdf/2306.02235 | https://neurips.cc/media/neurips-2023/Slides/73823.pdf |
QL ORA - Efficient Finetuning of Quantized LLMs | 2,023 | NeurIPS | Oral | 3 | null | 8 | Yes | null | 75,353 | 20 | Efficient Finetuning of Quantized Language Models;Low Rank Adaptation (LoRA);Memory Optimization Techniques;Chatbot Performance Evaluation | https://arxiv.org/pdf/2305.14314 | https://neurips.cc/media/neurips-2023/Slides/73855.pdf |
Learning to Segment Referred Objects from Narrated Egocentric Videos | 2,024 | CVPR | Oral | 4 | null | 3 | No | null | 55,536 | 17 | Weakly-Supervised Video Object Segmentation;Vision-Language Models;Contrastive Learning;Egocentric Video Analysis | https://openaccess.thecvf.com/content/CVPR2024/papers/Shen_Learning_to_Segment_Referred_Objects_from_Narrated_Egocentric_Videos_CVPR_2024_paper.pdf | https://cvpr.thecvf.com/media/cvpr-2024/Slides/29467.pdf |
CAMERAS AS RAYS - POSE ESTIMATION VIA RAY DIFFUSION | 2,024 | ICLR | Oral | 7 | null | 3 | Yes | null | 40,716 | 21 | Pose Estimation;Ray Diffusion;3D Reconstruction;Denoising Diffusion Models | https://arxiv.org/pdf/2402.14817 | https://iclr.cc/media/iclr-2024/Slides/19778.pdf |
CLIM ODE - C LIMATE AND WEATHER FORECASTING | 2,024 | ICLR | Oral | 8 | null | 3 | Yes | null | 35,588 | 35 | Physics-Informed Neural Networks;Weather Forecasting;Uncertainty Quantification;Spatiotemporal Modeling | https://arxiv.org/pdf/2404.10024 | https://iclr.cc/media/iclr-2024/Slides/19715.pdf |
LESS IS MORE - F EWER INTERPRETABLE REGION VIA | 2,024 | ICLR | Oral | 3 | null | 4 | Yes | null | 47,332 | 18 | Image Attribution;Submodular Optimization;Model Interpretability | https://arxiv.org/pdf/2402.09164 | https://iclr.cc/media/iclr-2024/Slides/19733.pdf |
METAGPT - M ETA PROGRAMMING FOR A MULTI-AGENT COLLABORATIVE FRAMEWORK | 2,024 | ICLR | Oral | 5 | null | 6 | Yes | null | 46,728 | 17 | Meta-Programming;Multi-Agent Systems;Large Language Models;Automated Problem Solving | https://arxiv.org/pdf/2308.00352 | https://iclr.cc/media/iclr-2024/Slides/18491.pdf |
A Touch, Vision, and Language Dataset for Multimodal Alignment | 2,024 | ICML | Oral | 6 | null | 4 | Yes | null | 42,012 | 48 | Multimodal Representation Learning;Tactile Data Annotation;Vision-Touch Language Alignment;Generative Language Models | https://arxiv.org/pdf/2402.13232 | https://icml.cc/media/icml-2024/Slides/35452.pdf |
APT - Adaptive Pruning and Tuning Pretrained Language Models for | 2,024 | ICML | Oral | 3 | null | 7 | Yes | null | 48,883 | 20 | Adaptive Pruning;Efficient Fine-Tuning;Parameter-Efficient Models;Language Model Optimization | https://arxiv.org/pdf/2401.12200 | https://icml.cc/media/icml-2024/Slides/35453.pdf |
Arrows_of_Time_for_Large_Language_Models | 2,024 | ICML | Oral | 4 | null | 5 | Yes | null | 52,767 | 85 | Autoregressive Language Modeling;Time Asymmetry in Probabilistic Models;Information Theory in AI Systems;Sparse Representation in Neural Networks | https://arxiv.org/pdf/2401.17505 | https://icml.cc/media/icml-2024/Slides/35521.pdf |
Bottleneck-Minimal Indexing for Generative Document Retrieval | 2,024 | ICML | Oral | 6 | null | 4 | Yes | null | 45,364 | 24 | Generative Document Retrieval;Information-Theoretic Approaches;Rate-Distortion Theory;Neural Autoregressive Models | https://arxiv.org/pdf/2405.10974 | https://icml.cc/media/icml-2024/Slides/35532.pdf |
Candidate Pseudolabel Learning - Enhancing Vision-Language Models by | 2,024 | ICML | Oral | 7 | null | 6 | Yes | null | 48,882 | 15 | Candidate Pseudolabel Learning;Vision-Language Models;Unlabeled Data Fine-tuning;Prompt Tuning | https://arxiv.org/pdf/2406.10502 | https://icml.cc/media/icml-2024/Slides/35456.pdf |
Challenges in Training PINNs - A Loss Landscape Perspective | 2,024 | ICML | Oral | 8 | null | 3 | Yes | null | 53,420 | 30 | Physics-Informed Neural Networks;Loss Landscape Optimization;Gradient-Based Optimization Methods;Partial Differential Equations | https://arxiv.org/pdf/2402.01868 | https://icml.cc/media/icml-2024/Slides/33180_kLYAzFO.pdf |
Data-free Neural Representation Compression | 2,024 | ICML | Oral | 3 | null | 5 | Yes | null | 47,302 | 18 | Riemannian Geometry in Neural Networks;Data-free Neural Network Compression;Dynamic Systems and Neural Representation;Neuronal Interaction Modeling | https://raw.githubusercontent.com/mlresearch/v235/main/assets/pei24d/pei24d.pdf | https://icml.cc/media/icml-2024/Slides/35536_gVhPtee.pdf |
ExCP - Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking | 2,024 | ICML | Oral | 5 | null | 7 | Yes | null | 42,889 | 14 | Checkpoint Compression;Weight-Momentum Optimization;Non-Uniform Quantization;Sparse Information Extraction | https://arxiv.org/pdf/2406.11257 | https://icml.cc/media/icml-2024/Slides/35484_oOBhtPf.pdf |
Expressivity and Generalization - Fragment-Biases for Molecular GNNs | 2,024 | ICML | Oral | 6 | null | 7 | Yes | null | 50,175 | 23 | Fragment-Biased Graph Neural Networks;Theoretic Expressivity Analysis;Molecular Property Prediction;Generalization in Machine Learning | https://arxiv.org/pdf/2406.08210 | https://icml.cc/media/icml-2024/Slides/35459.pdf |
Listenable Maps for Zero-Shot Audio Classifiers | 2,024 | ICML | Oral | 5 | null | 3 | Yes | null | 45,423 | 42 | Explainable AI;Zero-Shot Learning;Audio Classification;Post-Hoc Explanation Methods | https://arxiv.org/pdf/2405.17615 | https://icml.cc/media/icml-2024/Slides/33268.pdf |
MLLM-as-a-Judge - Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark | 2,024 | ICML | Oral | 9 | null | 8 | Yes | null | 61,182 | 33 | Multimodal Large Language Models;Benchmark Development;Judgment Biases in AI;Evaluation Metrics for AI Systems | https://arxiv.org/pdf/2402.04788 | https://icml.cc/media/icml-2024/Slides/35497.pdf |
MorphGrower - A Synchronized Layer-by-layer Growing Approach for | 2,024 | ICML | Oral | 5 | null | 3 | Yes | null | 49,482 | 19 | Neuronal Morphology Generation;Synchronized Layer-by-layer Growth;Topological Validity in Morphologies;Electrophysiological Response Simulation | https://arxiv.org/pdf/2401.09500 | https://icml.cc/media/icml-2024/Slides/35513.pdf |
Position - Rethinking Post-Hoc Search-Based Neural Approaches for Solving | 2,024 | ICML | Oral | 4 | null | 3 | Yes | null | 45,092 | 25 | Heatmap Generation for Optimization;Monte Carlo Tree Search;Traveling Salesman Problem;Combinatorial Optimization Methods | https://arxiv.org/pdf/2406.03503 | https://icml.cc/media/icml-2024/Slides/35505.pdf |
SparseTSF - Modeling Long-term Time Series Forecasting with 1k Parameters | 2,024 | ICML | Oral | 4 | null | 7 | Yes | null | 49,044 | 18 | Long-term Time Series Forecasting;Cross-Period Sparse Forecasting;Parameter Efficiency in Machine Learning Models;Generalization in Low-Resource Scenarios | https://arxiv.org/pdf/2405.00946 | https://icml.cc/media/icml-2024/Slides/35571.pdf |
Towards_Optimal_Adversarial_Robust_Q-learning_with_Bellman_Infinity-error | 2,024 | ICML | Oral | 5 | null | 3 | Yes | null | 54,693 | 30 | Adversarial Robustness in Reinforcement Learning;Optimal Robust Policy in Markov Decision Processes;Bellman Error Minimization Techniques;Deep Q-Networks Training Methods | https://arxiv.org/pdf/2402.02165 | https://icml.cc/media/icml-2024/Slides/33033_8TELIdY.pdf |
Unified_Training_of_Universal_Time_Series_Forecasting_Transformers | 2,024 | ICML | Oral | 6 | null | 7 | Yes | null | 57,564 | 39 | Universal Time Series Forecasting;Transformer Architectures;Cross-Frequency Learning;Multivariate Time Series Analysis | https://arxiv.org/pdf/2402.02592 | https://icml.cc/media/icml-2024/Slides/35515.pdf |
Video-of-Thought - Step-by-Step Video Reasoning from Perception to Cognition | 2,024 | ICML | Oral | 8 | null | 4 | Yes | null | 59,901 | 27 | Video Understanding;Spatial-Temporal Reasoning;Multimodal Large Language Models;Cognitive Video Comprehension | https://arxiv.org/pdf/2501.03230 | https://icml.cc/media/icml-2024/Slides/33467.pdf |
AgentBoard - An Analytical Evaluation Board of | 2,024 | NeurIPS | Oral | 6 | null | 7 | Yes | null | 59,530 | 62 | Evaluation Frameworks for Large Language Models;Multi-Turn Interaction in AI Agents;Benchmarking of Agent Performance;Interpretable AI | https://arxiv.org/pdf/2401.13178 | https://neurips.cc/media/neurips-2024/Slides/97853.pdf |
DapperFL - Domain Adaptive Federated Learning with | 2,024 | NeurIPS | Oral | 4 | null | 3 | Yes | null | 52,291 | 29 | Federated Learning;Domain Adaptation;Model Pruning;Edge Computing | https://arxiv.org/pdf/2412.05823 | https://neurips.cc/media/neurips-2024/Slides/95295.pdf |
Decompose, Analyze and Rethink | 2,024 | NeurIPS | Oral | 5 | null | 4 | Yes | null | 53,419 | 12 | Natural Language Processing;Reasoning in AI;Tree-based Question Decomposition;Large Language Models | https://proceedings.neurips.cc/paper_files/paper/2024/file/01025a4e79355bb37a10ba39605944b5-Paper-Conference.pdf | https://neurips.cc/media/neurips-2024/Slides/97984.pdf |
You Only Cache Once - Decoder-Decoder Architectures for Language Models | 2,024 | NeurIPS | Oral | 10 | null | 5 | Yes | null | 44,856 | 12 | Decoder-Decoder Architectures;Key-Value Caching Optimization;Transformer Model Efficiency;Global Attention Mechanisms | https://arxiv.org/pdf/2405.05254 | https://neurips.cc/media/neurips-2024/Slides/98001.pdf |
Geometric Knowledge-Guided Localized Global Distribution Alignment for Federated Learning | 2,025 | CVPR | Oral | 8 | null | 7 | No | null | 51,814 | 10 | Federated Learning;Data Heterogeneity;Geometric Distribution Alignment;Sample Generation Techniques | https://arxiv.org/pdf/2503.06457 | https://cvpr.thecvf.com/media/cvpr-2025/Slides/32823.pdf |
Deterministic Object Pose Confidence Region Estimation | 2,025 | ICCV | Oral | 6 | null | 6 | No | null | 44,266 | 27 | 6D Pose Estimation;Uncertainty Quantification;Deterministic Estimation Methods;Conformal Prediction | https://arxiv.org/pdf/2506.22720 | https://iccv.thecvf.com/media/iccv-2025/Slides/2258_KrNKhsn.pdf |
Diffusion Image Prior | 2,025 | ICCV | Oral | 7 | null | 6 | No | null | 35,462 | 22 | Diffusion Models;Image Restoration;Blind Image Restoration;Artifact Removal | https://arxiv.org/pdf/2503.21410 | https://iccv.thecvf.com/media/iccv-2025/Slides/2934.pdf |
Diving into the Fusion of Monocular Priors for Generalized Stereo Matching | 2,025 | ICCV | Oral | 4 | null | 7 | No | null | 48,476 | 35 | Stereo Matching;Monocular Depth Estimation;Depth Map Fusion;Ill-posed Problem Handling | https://arxiv.org/pdf/2505.14414 | https://iccv.thecvf.com/media/iccv-2025/Slides/2920_HA4wPU8.pdf |
Learning Streaming Video Representation via Multitask Training | 2,025 | ICCV | Oral | 3 | null | 6 | No | null | 62,845 | 19 | Streaming Video Representation;Multitask Learning;Online Action Detection;Video Question Answering | https://arxiv.org/pdf/2504.20041 | https://iccv.thecvf.com/media/iccv-2025/Slides/2901.pdf |
ACCELERATED TRAINING THROUGH ITERATIVE | 2,025 | ICLR | Oral | 6 | null | 4 | Yes | null | 44,150 | 14 | Highway Backpropagation;Residual Networks;Gradient Propagation Algorithms;Deep Learning Optimization | https://arxiv.org/pdf/2501.17086 | https://iclr.cc/media/iclr-2025/Slides/31872.pdf |
BOOSTER - T ACKLING HARMFUL FINE -TUNING FOR | 2,025 | ICLR | Oral | 3 | null | 9 | Yes | null | 61,851 | 16 | Harmful Fine-Tuning Attacks;Large Language Model Alignment;Loss Regularization Techniques | https://arxiv.org/pdf/2409.01586 | https://iclr.cc/media/iclr-2025/Slides/28050.pdf |
CHART MOE - M IXTURE OF DIVERSELY ALIGNED EX | 2,025 | ICLR | Oral | 11 | null | 8 | Yes | null | 58,200 | 13 | Chart Understanding;Mixture of Experts (MoE);Multimodal Large Language Models (MLLMs);Dataset Creation for Chart Analysis | https://arxiv.org/pdf/2409.03277 | https://iclr.cc/media/iclr-2025/Slides/31773.pdf |
CYBER HOST - A O NE-STAGE DIFFUSION FRAMEWORK | 2,025 | ICLR | Oral | 6 | null | 3 | Yes | null | 49,641 | 21 | Audio-Driven Talking Body Generation;Diffusion-Based Video Generation;Human Animation Synthesis;Region Attention Module in Animation | https://arxiv.org/pdf/2409.01876 | https://iclr.cc/media/iclr-2025/Slides/32123.pdf |
DEPT - D ECOUPLED EMBEDDINGS FOR PRE | 2,025 | ICLR | Oral | 5 | null | 13 | Yes | null | 67,319 | 23 | Decoupled Embeddings;Federated Learning;Language Model Pre-training;Communication-Efficient Training | https://arxiv.org/pdf/2410.05021 | https://iclr.cc/media/iclr-2025/Slides/27901_qTj5Ifm.pdf |
FLAT REWARD IN POLICY PARAMETER SPACE IMPLIES | 2,025 | ICLR | Oral | 7 | null | 3 | Yes | null | 48,254 | 30 | Flat Reward Landscapes;Robustness in Reinforcement Learning;Policy Parameter Space Analysis;Generalization in Deep Neural Networks | https://proceedings.iclr.cc/paper_files/paper/2025/file/3448058d44f133839042295f79a9a958-Paper-Conference.pdf | https://iclr.cc/media/iclr-2025/Slides/31923.pdf |
GESUBNET - G ENE INTERACTION INFERENCE FOR | 2,025 | ICLR | Oral | 6 | null | 4 | Yes | null | 54,038 | 21 | Gene Interaction Inference;Disease Subtype Network Generation;Graph Neural Networks;Representation Learning | https://arxiv.org/pdf/2410.13178 | https://iclr.cc/media/iclr-2025/Slides/28630_yPoleh1.pdf |
GRID MIX - E XPLORING SPATIAL MODULATION FOR | 2,025 | ICLR | Oral | 4 | null | 6 | Yes | null | 50,700 | 20 | Spatial Modulation;Neural Fields;Partial Differential Equations (PDE) Modeling;Domain Augmentation | https://openreview.net/pdf?id=Fur0DtynPX | https://iclr.cc/media/iclr-2025/Slides/31883.pdf |
IMPROVING PROBABILISTIC DIFFUSION MODELS WITH | 2,025 | ICLR | Oral | 4 | null | 8 | Yes | null | 51,204 | 43 | Probabilistic Diffusion Models;Optimal Covariance Matching;Denoising Distribution;Sampling Efficiency | https://arxiv.org/pdf/2406.10808 | https://iclr.cc/media/iclr-2025/Slides/28877.pdf |
IMPROVING PROBABILISTIC DIFFUSION MODELS WITH (2) | 2,025 | ICLR | Oral | 4 | null | 8 | Yes | null | 51,204 | 17 | Probabilistic Diffusion Models;Diagonal Covariance Matching;Optimal Covariance Matching;Sampling Efficiency | https://arxiv.org/pdf/2410.13708 | https://iclr.cc/media/iclr-2025/Slides/28788.pdf |
Inference_Scaling_for_Long-Context_Retrieval_Augmented_Generation | 2,025 | ICLR | Oral | 8 | null | 4 | Yes | null | 46,464 | 38 | Long-Context Large Language Models;Retrieval Augmented Generation;Inference Scaling Laws;Optimal Computation Allocation | https://arxiv.org/pdf/2410.04343 | https://iclr.cc/media/iclr-2025/Slides/30339.pdf |
KNOWING YOUR TARGET - TARGET -AWARE TRANSFORMER MAKES BETTER SPATIO-T EMPORAL | 2,025 | ICLR | Oral | 6 | null | 10 | Yes | null | 52,853 | 17 | Spatio-Temporal Video Grounding;Target-Aware Transformers;Multimodal Feature Interactions;Object Query Initialization | https://arxiv.org/pdf/2502.11168 | https://iclr.cc/media/iclr-2025/Slides/29364.pdf |
LEARNING TO DISCRETIZE | 2,025 | ICLR | Oral | 6 | null | 8 | Yes | null | 49,108 | 29 | Diffusion Probabilistic Models;Sampling Efficiency;Neural Function Evaluations;Generative Model Optimization | https://arxiv.org/pdf/2405.15506 | https://iclr.cc/media/iclr-2025/Slides/31735.pdf |
MEASURING AND ENHANCING TRUSTWORTHINESS OF | 2,025 | ICLR | Oral | 3 | null | 10 | Yes | null | 65,340 | 39 | Trustworthiness Evaluation in LLMs;Retrieval-Augmented Generation (RAG);Prompting Methods for LLMs;Model Alignment Techniques | https://arxiv.org/pdf/2409.11242 | https://iclr.cc/media/iclr-2025/Slides/31873.pdf |
NEURAL PLANE - S TRUCTURED 3D R ECONSTRUCTION | 2,025 | ICLR | Oral | 7 | null | 3 | Yes | null | 48,329 | 16 | 3D Plane Reconstruction;Neural Fields;Self-Supervised Learning;Semantic Segmentation | https://openreview.net/pdf?id=5UKrnKuspb | https://iclr.cc/media/iclr-2025/Slides/30944.pdf |
Navigating the Digital World as Humans Do | 2,025 | ICLR | Oral | 5 | null | 9 | Yes | null | 61,854 | 26 | Visual Grounding;Multimodal Learning;Graphical User Interface (GUI) Agents;Synthetic Data Generation | https://arxiv.org/pdf/2410.05243 | https://iclr.cc/media/iclr-2025/Slides/32124.pdf |
OPEN -VOCABULARY OBJECT DETECTION VIA | 2,025 | ICLR | Oral | 7 | null | 6 | Yes | null | 48,188 | 12 | Open-Vocabulary Object Detection;Knowledge Distillation;Vision and Language Integration;Transfer Learning | https://arxiv.org/pdf/2104.13921 | https://iclr.cc/media/iclr-2025/Slides/31930.pdf |
Open-YOLO 3D - Towards Fast and Accurate Open-Vocabulary 3D Instance Segmentation | 2,025 | ICLR | Oral | 4 | null | 5 | Yes | null | 38,184 | 17 | Open-Vocabulary 3D Instance Segmentation;2D Object Detection;Multi-View Image Processing;Real-Time Inference Techniques | https://arxiv.org/pdf/2406.02548 | https://iclr.cc/media/iclr-2025/Slides/31900_8PUpb67.pdf |
PROBABILISTIC LEARNING TO DEFER - H ANDLING | 2,025 | ICLR | Oral | 5 | null | 3 | Yes | null | 47,151 | 47 | Learning to Defer;Probabilistic Modelling;Workload Distribution in Human-AI Cooperation;Handling Missing Annotations | https://openreview.net/pdf?id=zl0HLZOJC9 | https://iclr.cc/media/iclr-2025/Slides/31728.pdf |
REPRESENTATION ALIGNMENT FOR GENERATION | 2,025 | ICLR | Oral | 8 | null | 5 | Yes | null | 61,444 | 19 | Representation Alignment;Denoising Diffusion Models;Visual Representation Learning;Training Efficiency in Generative Models | https://arxiv.org/pdf/2410.06940 | https://iclr.cc/media/iclr-2025/Slides/31896.pdf |
SD-L ORA - S CALABLE DECOUPLED LOW-RANK ADAP | 2,025 | ICLR | Oral | 5 | null | 5 | Yes | null | 46,379 | 28 | Class Incremental Learning;Low-Rank Adaptation;Scalable Machine Learning;Continual Learning | https://arxiv.org/pdf/2501.13198 | https://iclr.cc/media/iclr-2025/Slides/31918.pdf |
SPIDER 2.0 - E VALUATING LANGUAGE MODELS ON | 2,025 | ICLR | Oral | 18 | null | 18 | Yes | null | 58,210 | 23 | Text-to-SQL Transformation;SQL Query Generation;Model Evaluation Frameworks;Enterprise Database Systems | https://arxiv.org/pdf/2411.07763 | https://iclr.cc/media/iclr-2025/Slides/31826.pdf |
STANDARD GAUSSIAN PROCESS IS ALL YOU NEED FOR | 2,025 | ICLR | Oral | 5 | null | 4 | Yes | null | 44,476 | 24 | Bayesian Optimization;Gaussian Processes;Matérn Kernels;High-Dimensional Optimization | https://arxiv.org/pdf/2402.02746 | https://iclr.cc/media/iclr-2025/Slides/31784.pdf |
TIME MIXER ++ - A G ENERAL TIME SERIES PATTERN | 2,025 | ICLR | Oral | 5 | null | 10 | Yes | null | 59,545 | 18 | Time Series Analysis;Pattern Extraction;Multi-Resolution Time Imaging;Anomaly Detection | https://arxiv.org/pdf/2410.16032 | https://iclr.cc/media/iclr-2025/Slides/31932.pdf |
TOWARD GUIDANCE -F REE AR V ISUAL GENERATION | 2,025 | ICLR | Oral | 8 | null | 3 | Yes | null | 60,033 | 26 | Classifier-Free Guidance;Autoregressive Visual Generation;Contrastive Learning;Multi-Modal Alignment | https://arxiv.org/pdf/2410.09347 | https://iclr.cc/media/iclr-2025/Slides/31786.pdf |
UNLOCKING STATE-TRACKING IN LINEAR RNN S | 2,025 | ICLR | Oral | 9 | null | 5 | Yes | null | 56,524 | 22 | Linear Recurrent Neural Networks;State-Tracking in Neural Networks;Eigenvalue Analysis in Neural Networks;Language Modeling | https://arxiv.org/pdf/2411.12537 | https://iclr.cc/media/iclr-2025/Slides/31836.pdf |
miniCTX - NEURAL THEOREM PROVING WITH (LONG -) CONTEXTS | 2,025 | ICLR | Oral | 5 | null | 5 | Yes | null | 49,565 | 26 | Neural Theorem Proving;Contextual Reasoning;Interactive Theorem Provers;Fine-Tuning Language Models | https://arxiv.org/pdf/2408.03350 | https://iclr.cc/media/iclr-2025/Slides/31870.pdf |
Can MLLMs Reason in Multimodality | 2,025 | ICML | Oral | 8 | null | 3 | Yes | null | 45,918 | 45 | Multimodal Reasoning;Benchmark Development;Cross-Modal Reasoning Tasks;Large Language Models Evaluation | https://arxiv.org/pdf/2501.05444 | https://icml.cc/media/icml-2025/Slides/47178_idf0Qr8.pdf |
Foundation Model Insights and a Multi-Model Approach for | 2,025 | ICML | Oral | 4 | null | 3 | Yes | null | 50,190 | 36 | One-Shot Subset Selection;Foundation Models;Fine-Grained Image Datasets;Data Efficiency in Deep Learning | https://arxiv.org/pdf/2506.14473 | https://icml.cc/media/icml-2025/Slides/47211.pdf |
Learning with Expected Signatures - Theory and Applications | 2,025 | ICML | Oral | 3 | null | 3 | Yes | null | 46,366 | 13 | Expected Signatures;Time Series Analysis;Martingale Processes;Probabilistic Machine Learning | https://arxiv.org/pdf/2505.20465 | https://icml.cc/media/icml-2025/Slides/43548.pdf |
LoRA-One - One-Step Full Gradient Could Suffice for Fine-Tuning Large | 2,025 | ICML | Oral | 5 | null | 5 | Yes | null | 45,295 | 24 | Low-Rank Adaptation;Gradient Descent Optimization;Fine-Tuning Large Language Models;Theory-Driven Algorithm Design | https://arxiv.org/pdf/2502.01235 | https://icml.cc/media/icml-2025/Slides/47237.pdf |
Model_Immunization_from_a_Condition_Number_Perspective | 2,025 | ICML | Oral | 3 | null | 3 | Yes | null | 42,978 | 20 | Model Immunization;Condition Number Analysis;Hessian Matrix Regularization;Non-Harmful Task Retention | https://arxiv.org/pdf/2505.23760 | https://icml.cc/media/icml-2025/Slides/47180.pdf |
Position - Current Model Licensing Practices are Dragging Us into a Quagmire of Legal Noncompliance | 2,025 | ICML | Oral | 9 | null | 4 | Yes | null | 44,267 | 9 | Model Licensing Practices;Legal Compliance in AI;Standardization of ML Licenses;Risks of License Noncompliance | https://raw.githubusercontent.com/mlresearch/v267/main/assets/duan25d/duan25d.pdf | https://icml.cc/media/icml-2025/Slides/40180_4s09QZJ.pdf |
Sundial - A Family of Highly Capable Time Series Foundation Models | 2,025 | ICML | Oral | 10 | null | 7 | Yes | null | 57,288 | 27 | Time Series Forecasting;Transformers in Time Series;Generative Forecasting Models;Probabilistic Prediction Techniques | https://arxiv.org/pdf/2502.00816 | https://icml.cc/media/icml-2025/Slides/45591_NN9Y4k8.pdf |
VideoRoPE - What Makes for Good Video Rotary Position Embedding | 2,025 | ICML | Oral | 7 | null | 5 | Yes | null | 48,167 | 17 | Rotary Position Embedding;Spatio-Temporal Analysis;Video Retrieval;Video Understanding | https://arxiv.org/pdf/2502.05173 | https://icml.cc/media/icml-2025/Slides/47183.pdf |
Adaptive Surrogate Gradients for Sequential | 2,025 | NeurIPS | Oral | 5 | null | 7 | No | null | 50,102 | 60 | Spiking Neural Networks;Surrogate Gradient Optimization;Reinforcement Learning;Neuromorphic Computing | https://arxiv.org/pdf/2510.24461 | https://nips.cc/media/neurips-2025/Slides/116055.pdf |
Dynam3D - Dynamic Layered 3D Tokens Empower VLM for Vision-and-Language Navigation | 2,025 | NeurIPS | Oral | 4 | null | 6 | Yes | null | 49,369 | 13 | Vision-and-Language Navigation;3D Object Recognition;Dynamic 3D Representation;Long-Term Environmental Memory | https://arxiv.org/pdf/2505.11383 | https://nips.cc/media/neurips-2025/Slides/115716.pdf |
GNNXEMPLAR - Exemplars to Explanations - Natural | 2,025 | NeurIPS | Oral | 11 | null | 3 | Yes | null | 70,794 | 41 | Graph Neural Networks;Global Explainability;Natural Language Processing;Exemplar Selection | https://arxiv.org/pdf/2509.18376 | https://neurips.cc/media/neurips-2025/Slides/116902.pdf |
OpenHOI - Open-World Hand-Object Interaction | 2,025 | NeurIPS | Oral | 3 | null | 5 | Yes | null | 44,988 | 20 | Open-World Hand-Object Interaction;Multimodal Large Language Models;Affordance-driven Diffusion Models;Complex Language Instruction Decomposition | https://arxiv.org/pdf/2505.18947 | https://neurips.cc/media/neurips-2025/Slides/120304.pdf |
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