| topic_id,topic_label,rank,paper_id,year,title,decision,avg_rating,avg_rating_z_year,topic_prob,openreview_url,semantic_scholar_search_url |
| 0,0_policy_rl_reinforcement_the,1,pGEY8JQ3qx,2024,Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs,Accept (oral),7.75,1.5882980506982585,1.0,https://openreview.net/forum?id=pGEY8JQ3qx,https://www.semanticscholar.org/search?q=Span-Based+Optimal+Sample+Complexity+for+Weakly+Communicating+and+General+Average+Reward+MDPs |
| 0,0_policy_rl_reinforcement_the,2,cYZibc2gKf,2024,Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation,Accept (poster),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=cYZibc2gKf,https://www.semanticscholar.org/search?q=Abstract+Reward+Processes%3A+Leveraging+State+Abstraction+for+Consistent+Off-Policy+Evaluation |
| 0,0_policy_rl_reinforcement_the,3,fu0xdh4aEJ,2024,"Bigger, Regularized, Optimistic: scaling for compute and sample efficient continuous control",Accept (spotlight),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=fu0xdh4aEJ,https://www.semanticscholar.org/search?q=Bigger%2C+Regularized%2C+Optimistic%3A+scaling+for+compute+and+sample+efficient+continuous+control |
| 0,0_policy_rl_reinforcement_the,4,hH4bPkOhhh,2024,Identifying Selections for Unsupervised Subtask Discovery,Accept (poster),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=hH4bPkOhhh,https://www.semanticscholar.org/search?q=Identifying+Selections+for+Unsupervised+Subtask+Discovery |
| 0,0_policy_rl_reinforcement_the,5,QFUsZvw9mx,2024,Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning,Accept (spotlight),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=QFUsZvw9mx,https://www.semanticscholar.org/search?q=Towards+an+Information+Theoretic+Framework+of+Context-Based+Offline+Meta-Reinforcement+Learning |
| 1,1_3d_and_scene_to,1,x7pjdDod6Z,2024,MeshFormer : High-Quality Mesh Generation with 3D-Guided Reconstruction Model,Accept (oral),7.2,1.1246333394379104,1.0,https://openreview.net/forum?id=x7pjdDod6Z,https://www.semanticscholar.org/search?q=MeshFormer+%3A+High-Quality+Mesh+Generation+with+3D-Guided+Reconstruction+Model |
| 1,1_3d_and_scene_to,2,TFZlFRl9Ks,2024,CAT3D: Create Anything in 3D with Multi-View Diffusion Models,Accept (oral),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=TFZlFRl9Ks,https://www.semanticscholar.org/search?q=CAT3D%3A+Create+Anything+in+3D+with+Multi-View+Diffusion+Models |
| 1,1_3d_and_scene_to,3,1IOU2329Za,2023,Banana: Banach Fixed-Point Network for Pointcloud Segmentation with Inter-Part Equivariance,Accept (spotlight),6.8,0.757902568734561,1.0,https://openreview.net/forum?id=1IOU2329Za,https://www.semanticscholar.org/search?q=Banana%3A+Banach+Fixed-Point+Network+for+Pointcloud+Segmentation+with+Inter-Part+Equivariance |
| 1,1_3d_and_scene_to,4,KgqucdSwIe,2023,VoxDet: Voxel Learning for Novel Instance Detection,Accept (spotlight),6.8,0.757902568734561,1.0,https://openreview.net/forum?id=KgqucdSwIe,https://www.semanticscholar.org/search?q=VoxDet%3A+Voxel+Learning+for+Novel+Instance+Detection |
| 1,1_3d_and_scene_to,5,6AeIDnrTN2,2024,LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS,Accept (spotlight),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=6AeIDnrTN2,https://www.semanticscholar.org/search?q=LightGaussian%3A+Unbounded+3D+Gaussian+Compression+with+15x+Reduction+and+200%2B+FPS |
| 2,2_diffusion_image_the_of,1,gojL67CfS8,2024,Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction,Accept (oral),7.75,1.5882980506982585,1.0,https://openreview.net/forum?id=gojL67CfS8,https://www.semanticscholar.org/search?q=Visual+Autoregressive+Modeling%3A+Scalable+Image+Generation+via+Next-Scale+Prediction |
| 2,2_diffusion_image_the_of,2,3Odq2tGSpp,2024,Stylus: Automatic Adapter Selection for Diffusion Models,Accept (oral),7.5,1.3775413637617366,1.0,https://openreview.net/forum?id=3Odq2tGSpp,https://www.semanticscholar.org/search?q=Stylus%3A+Automatic+Adapter+Selection+for+Diffusion+Models |
| 2,2_diffusion_image_the_of,3,NnMEadcdyD,2023,Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation,Accept (oral),7.4,1.2604663214348872,1.0,https://openreview.net/forum?id=NnMEadcdyD,https://www.semanticscholar.org/search?q=Understanding+Diffusion+Objectives+as+the+ELBO+with+Simple+Data+Augmentation |
| 2,2_diffusion_image_the_of,4,fqmSGK8C0B,2024,Deep Learning for Computing Convergence Rates of Markov Chains,Accept (spotlight),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=fqmSGK8C0B,https://www.semanticscholar.org/search?q=Deep+Learning+for+Computing+Convergence+Rates+of+Markov+Chains |
| 2,2_diffusion_image_the_of,5,bg6fVPVs3s,2024,Guiding a Diffusion Model with a Bad Version of Itself,Accept (oral),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=bg6fVPVs3s,https://www.semanticscholar.org/search?q=Guiding+a+Diffusion+Model+with+a+Bad+Version+of+Itself |
| 3,3_multimodal_visual_and_to,1,lA48H7pW3q,2024,QUEST: Quadruple Multimodal Contrastive Learning with Constraints and Self-Penalization,Accept (poster),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=lA48H7pW3q,https://www.semanticscholar.org/search?q=QUEST%3A+Quadruple+Multimodal+Contrastive+Learning+with+Constraints+and+Self-Penalization |
| 3,3_multimodal_visual_and_to,2,XgwTH95kCl,2024,Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=XgwTH95kCl,https://www.semanticscholar.org/search?q=Toward+Robust+Incomplete+Multimodal+Sentiment+Analysis+via+Hierarchical+Representation+Learning |
| 3,3_multimodal_visual_and_to,3,4D7hnJ9oM6,2024,WATT: Weight Average Test Time Adaptation of CLIP,Accept (poster),7.0,0.9560279898886929,1.0,https://openreview.net/forum?id=4D7hnJ9oM6,https://www.semanticscholar.org/search?q=WATT%3A+Weight+Average+Test+Time+Adaptation+of+CLIP |
| 3,3_multimodal_visual_and_to,4,7xlrdSOm3g,2023,A Theory of Multimodal Learning,Accept (poster),6.8,0.7579025687345609,1.0,https://openreview.net/forum?id=7xlrdSOm3g,https://www.semanticscholar.org/search?q=A+Theory+of+Multimodal+Learning |
| 3,3_multimodal_visual_and_to,5,Q9CNA7B7v2,2023,SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process,Accept (poster),6.8,0.757902568734561,1.0,https://openreview.net/forum?id=Q9CNA7B7v2,https://www.semanticscholar.org/search?q=SegRefiner%3A+Towards+Model-Agnostic+Segmentation+Refinement+with+Discrete+Diffusion+Process |
| 4,4_graph_graphs_gnns_node,1,jgkKroLxeC,2024,Unified Graph Augmentations for Generalized Contrastive Learning on Graphs,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=jgkKroLxeC,https://www.semanticscholar.org/search?q=Unified+Graph+Augmentations+for+Generalized+Contrastive+Learning+on+Graphs |
| 4,4_graph_graphs_gnns_node,2,y8P633E5HQ,2024,Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters,Accept (poster),6.6,0.6188172907902577,1.0,https://openreview.net/forum?id=y8P633E5HQ,https://www.semanticscholar.org/search?q=Equivariant+Machine+Learning+on+Graphs+with+Nonlinear+Spectral+Filters |
| 4,4_graph_graphs_gnns_node,3,jt10uWlEbc,2023,Fine-grained Expressivity of Graph Neural Networks,Accept (poster),6.6,0.5903813178344521,1.0,https://openreview.net/forum?id=jt10uWlEbc,https://www.semanticscholar.org/search?q=Fine-grained+Expressivity+of+Graph+Neural+Networks |
| 4,4_graph_graphs_gnns_node,4,JDAQwysFOc,2024,Non-convolutional graph neural networks.,Accept (spotlight),6.5,0.534514616015649,1.0,https://openreview.net/forum?id=JDAQwysFOc,https://www.semanticscholar.org/search?q=Non-convolutional+graph+neural+networks. |
| 4,4_graph_graphs_gnns_node,5,p8lowHbuv8,2023,From Trainable Negative Depth to Edge Heterophily in Graphs,Accept (poster),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=p8lowHbuv8,https://www.semanticscholar.org/search?q=From+Trainable+Negative+Depth+to+Edge+Heterophily+in+Graphs |
| 5,5_regret_the_bandits_bandit,1,Q4NWfStqVf,2024,Nearly Minimax Optimal Regret for Multinomial Logistic Bandit,Accept (poster),7.4,1.293238688987128,1.0,https://openreview.net/forum?id=Q4NWfStqVf,https://www.semanticscholar.org/search?q=Nearly+Minimax+Optimal+Regret+for+Multinomial+Logistic+Bandit |
| 5,5_regret_the_bandits_bandit,2,RYQ0KuZvkL,2024,Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning,Accept (spotlight),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=RYQ0KuZvkL,https://www.semanticscholar.org/search?q=Sample+Complexity+Reduction+via+Policy+Difference+Estimation+in+Tabular+Reinforcement+Learning |
| 5,5_regret_the_bandits_bandit,3,TXoZiUZywf,2023,Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures,Accept (oral),7.25,1.1348253832598056,1.0,https://openreview.net/forum?id=TXoZiUZywf,https://www.semanticscholar.org/search?q=Improved+Algorithms+for+Stochastic+Linear+Bandits+Using+Tail+Bounds+for+Martingale+Mixtures |
| 5,5_regret_the_bandits_bandit,4,XfYpIaKDb6,2023,On the Minimax Regret for Online Learning with Feedback Graphs,Accept (spotlight),7.25,1.1348253832598056,1.0,https://openreview.net/forum?id=XfYpIaKDb6,https://www.semanticscholar.org/search?q=On+the+Minimax+Regret+for+Online+Learning+with+Feedback+Graphs |
| 5,5_regret_the_bandits_bandit,5,dY4YGqvfgW,2024,On Weak Regret Analysis for Dueling Bandits,Accept (poster),7.0,0.9560279898886929,1.0,https://openreview.net/forum?id=dY4YGqvfgW,https://www.semanticscholar.org/search?q=On+Weak+Regret+Analysis+for+Dueling+Bandits |
| 6,6_brain_spiking_of_and,1,qTypwXvNJa,2024,Geodesic Optimization for Predictive Shift Adaptation on EEG data,Accept (spotlight),7.5,1.3775413637617366,1.0,https://openreview.net/forum?id=qTypwXvNJa,https://www.semanticscholar.org/search?q=Geodesic+Optimization+for+Predictive+Shift+Adaptation+on+EEG+data |
| 6,6_brain_spiking_of_and,2,AbTpJl7vN6,2024,Flexible task abstractions emerge in linear networks with fast and bounded units,Accept (spotlight),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=AbTpJl7vN6,https://www.semanticscholar.org/search?q=Flexible+task+abstractions+emerge+in+linear+networks+with+fast+and+bounded+units |
| 6,6_brain_spiking_of_and,3,nw9JmfL99s,2024,Nonlinear dynamics of localization in neural receptive fields,Accept (spotlight),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=nw9JmfL99s,https://www.semanticscholar.org/search?q=Nonlinear+dynamics+of+localization+in+neural+receptive+fields |
| 6,6_brain_spiking_of_and,4,OQzCSb6fbl,2024,Parallel Backpropagation for Shared-Feature Visualization,Accept (spotlight),7.25,1.1667846768252146,1.0,https://openreview.net/forum?id=OQzCSb6fbl,https://www.semanticscholar.org/search?q=Parallel+Backpropagation+for+Shared-Feature+Visualization |
| 6,6_brain_spiking_of_and,5,u39QQh5L8Q,2023,Uncovering motifs of concurrent signaling across multiple neuronal populations,Accept (spotlight),7.25,1.1348253832598056,1.0,https://openreview.net/forum?id=u39QQh5L8Q,https://www.semanticscholar.org/search?q=Uncovering+motifs+of+concurrent+signaling+across+multiple+neuronal+populations |
| 7,7_protein_molecular_and_drug,1,WPdGRRJaPb,2023,Full-Atom Protein Pocket Design via Iterative Refinement,Accept (spotlight),7.6,1.427987572334996,1.0,https://openreview.net/forum?id=WPdGRRJaPb,https://www.semanticscholar.org/search?q=Full-Atom+Protein+Pocket+Design+via+Iterative+Refinement |
| 7,7_protein_molecular_and_drug,2,WyVTj77KEV,2024,Generalized Protein Pocket Generation with Prior-Informed Flow Matching,Accept (spotlight),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=WyVTj77KEV,https://www.semanticscholar.org/search?q=Generalized+Protein+Pocket+Generation+with+Prior-Informed+Flow+Matching |
| 7,7_protein_molecular_and_drug,3,gipFTlvfF1,2024,Conditional Synthesis of 3D Molecules with Time Correction Sampler,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=gipFTlvfF1,https://www.semanticscholar.org/search?q=Conditional+Synthesis+of+3D+Molecules+with+Time+Correction+Sampler |
| 7,7_protein_molecular_and_drug,4,OEWBkLrRZu,2024,Towards Stable Representations for Protein Interface Prediction,Accept (poster),6.333333333333333,0.39401015805796763,1.0,https://openreview.net/forum?id=OEWBkLrRZu,https://www.semanticscholar.org/search?q=Towards+Stable+Representations+for+Protein+Interface+Prediction |
| 7,7_protein_molecular_and_drug,5,Eb74zfBkWa,2023,Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering,Accept (poster),6.25,0.2972191287592618,1.0,https://openreview.net/forum?id=Eb74zfBkWa,https://www.semanticscholar.org/search?q=Disentangled+Wasserstein+Autoencoder+for+T-Cell+Receptor+Engineering |
| 8,8_reasoning_llms_language_to,1,VqkAKQibpq,2024,SGLang: Efficient Execution of Structured Language Model Programs,Accept (poster),7.4,1.293238688987128,1.0,https://openreview.net/forum?id=VqkAKQibpq,https://www.semanticscholar.org/search?q=SGLang%3A+Efficient+Execution+of+Structured+Language+Model+Programs |
| 8,8_reasoning_llms_language_to,2,rcXXNFVlEn,2023,Why think step by step? Reasoning emerges from the locality of experience,Accept (oral),7.25,1.1348253832598056,1.0,https://openreview.net/forum?id=rcXXNFVlEn,https://www.semanticscholar.org/search?q=Why+think+step+by+step%3F+Reasoning+emerges+from+the+locality+of+experience |
| 8,8_reasoning_llms_language_to,3,NPKZF1WDjZ,2024,"Decompose, Analyze and Rethink: Solving Intricate Problems with Human-like Reasoning Cycle",Accept (oral),6.8,0.7874226403394753,1.0,https://openreview.net/forum?id=NPKZF1WDjZ,https://www.semanticscholar.org/search?q=Decompose%2C+Analyze+and+Rethink%3A+Solving+Intricate+Problems+with+Human-like+Reasoning+Cycle |
| 8,8_reasoning_llms_language_to,4,e397soEZh8,2024,Learning Structure-Aware Representations of Dependent Types,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=e397soEZh8,https://www.semanticscholar.org/search?q=Learning+Structure-Aware+Representations+of+Dependent+Types |
| 8,8_reasoning_llms_language_to,5,qVMPXrX4FR,2023,LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas,Accept (poster),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=qVMPXrX4FR,https://www.semanticscholar.org/search?q=LambdaBeam%3A+Neural+Program+Search+with+Higher-Order+Functions+and+Lambdas |
| 9,9_causal_treatment_variables_of,1,OIsUWQSvkD,2024,Identifying Causal Effects Under Functional Dependencies,Accept (spotlight),7.5,1.3775413637617366,1.0,https://openreview.net/forum?id=OIsUWQSvkD,https://www.semanticscholar.org/search?q=Identifying+Causal+Effects+Under+Functional+Dependencies |
| 9,9_causal_treatment_variables_of,2,q131tA7HCT,2023,Learning Linear Causal Representations from Interventions under General Nonlinear Mixing,Accept (oral),7.5,1.3442269468849415,1.0,https://openreview.net/forum?id=q131tA7HCT,https://www.semanticscholar.org/search?q=Learning+Linear+Causal+Representations+from+Interventions+under+General+Nonlinear+Mixing |
| 9,9_causal_treatment_variables_of,3,4rCZeCZAON,2024,Do Finetti: On Causal Effects for Exchangeable Data,Accept (oral),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=4rCZeCZAON,https://www.semanticscholar.org/search?q=Do+Finetti%3A+On+Causal+Effects+for+Exchangeable+Data |
| 9,9_causal_treatment_variables_of,4,QIFoCI7ca1,2023,Causal normalizing flows: from theory to practice,Accept (oral),7.2,1.0929450705347785,1.0,https://openreview.net/forum?id=QIFoCI7ca1,https://www.semanticscholar.org/search?q=Causal+normalizing+flows%3A+from+theory+to+practice |
| 9,9_causal_treatment_variables_of,5,weemASPtzg,2024,Linear Causal Representation Learning from Unknown Multi-node Interventions,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=weemASPtzg,https://www.semanticscholar.org/search?q=Linear+Causal+Representation+Learning+from+Unknown+Multi-node+Interventions |
| 10,10_privacy_private_dp_differentially,1,PITeSdYQkv,2023,User-Level Differential Privacy With Few Examples Per User,Accept (oral),7.5,1.3442269468849415,1.0,https://openreview.net/forum?id=PITeSdYQkv,https://www.semanticscholar.org/search?q=User-Level+Differential+Privacy+With+Few+Examples+Per+User |
| 10,10_privacy_private_dp_differentially,2,7yjsYrajlt,2023,The Target-Charging Technique for Privacy Analysis across Interactive Computations,Accept (poster),6.833333333333333,0.7858227772179124,1.0,https://openreview.net/forum?id=7yjsYrajlt,https://www.semanticscholar.org/search?q=The+Target-Charging+Technique+for+Privacy+Analysis+across+Interactive+Computations |
| 10,10_privacy_private_dp_differentially,3,BAjjINf0Oh,2024,Oracle-Efficient Differentially Private Learning with Public Data,Accept (poster),6.8,0.7874226403394752,1.0,https://openreview.net/forum?id=BAjjINf0Oh,https://www.semanticscholar.org/search?q=Oracle-Efficient+Differentially+Private+Learning+with+Public+Data |
| 10,10_privacy_private_dp_differentially,4,CgGjT8EG8A,2024,Universal Exact Compression of Differentially Private Mechanisms,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=CgGjT8EG8A,https://www.semanticscholar.org/search?q=Universal+Exact+Compression+of+Differentially+Private+Mechanisms |
| 10,10_privacy_private_dp_differentially,5,izNfcaHJk0,2023,Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation,Accept (poster),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=izNfcaHJk0,https://www.semanticscholar.org/search?q=Privacy+Amplification+via+Compression%3A+Achieving+the+Optimal+Privacy-Accuracy-Communication+Trade-off+in+Distributed+Mean+Estimation |
| 11,11_series_time_forecasting_data,1,DV15UbHCY1,2024,Are Language Models Actually Useful for Time Series Forecasting?,Accept (spotlight),7.25,1.1667846768252146,1.0,https://openreview.net/forum?id=DV15UbHCY1,https://www.semanticscholar.org/search?q=Are+Language+Models+Actually+Useful+for+Time+Series+Forecasting%3F |
| 11,11_series_time_forecasting_data,2,clBiQUgj4w,2024,CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns,Accept (spotlight),7.25,1.1667846768252146,1.0,https://openreview.net/forum?id=clBiQUgj4w,https://www.semanticscholar.org/search?q=CycleNet%3A+Enhancing+Time+Series+Forecasting+through+Modeling+Periodic+Patterns |
| 11,11_series_time_forecasting_data,3,wiEHZSV15I,2024,Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting,Accept (spotlight),6.666666666666667,0.6750190739733303,1.0,https://openreview.net/forum?id=wiEHZSV15I,https://www.semanticscholar.org/search?q=Parsimony+or+Capability%3F+Decomposition+Delivers+Both+in+Long-term+Time+Series+Forecasting |
| 11,11_series_time_forecasting_data,4,FOvZztnp1H,2024,AutoTimes: Autoregressive Time Series Forecasters via Large Language Models,Accept (poster),6.25,0.32375792907912704,1.0,https://openreview.net/forum?id=FOvZztnp1H,https://www.semanticscholar.org/search?q=AutoTimes%3A+Autoregressive+Time+Series+Forecasters+via+Large+Language+Models |
| 11,11_series_time_forecasting_data,5,B1Iq1EOiVU,2024,DeformableTST: Transformer for Time Series Forecasting without Over-reliance on Patching,Accept (poster),6.25,0.32375792907912704,1.0,https://openreview.net/forum?id=B1Iq1EOiVU,https://www.semanticscholar.org/search?q=DeformableTST%3A+Transformer+for+Time+Series+Forecasting+without+Over-reliance+on+Patching |
| 12,12_adversarial_attacks_robustness_attack,1,MN4nt01TeO,2024,Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences,Accept (spotlight),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=MN4nt01TeO,https://www.semanticscholar.org/search?q=Adaptive+Randomized+Smoothing%3A+Certified+Adversarial+Robustness+for+Multi-Step+Defences |
| 12,12_adversarial_attacks_robustness_attack,2,MPidsCd9e7,2024,Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=MPidsCd9e7,https://www.semanticscholar.org/search?q=Adversarially+Robust+Dense-Sparse+Tradeoffs+via+Heavy-Hitters |
| 12,12_adversarial_attacks_robustness_attack,3,iT9MOAZqsb,2023,Adversarial Training from Mean Field Perspective,Accept (spotlight),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=iT9MOAZqsb,https://www.semanticscholar.org/search?q=Adversarial+Training+from+Mean+Field+Perspective |
| 12,12_adversarial_attacks_robustness_attack,4,xbbknN9QFs,2023,On Evaluating Adversarial Robustness of Large Vision-Language Models,Accept (poster),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=xbbknN9QFs,https://www.semanticscholar.org/search?q=On+Evaluating+Adversarial+Robustness+of+Large+Vision-Language+Models |
| 12,12_adversarial_attacks_robustness_attack,5,K8gLHZIgVW,2023,Regularization properties of adversarially-trained linear regression,Accept (spotlight),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=K8gLHZIgVW,https://www.semanticscholar.org/search?q=Regularization+properties+of+adversarially-trained+linear+regression |
| 13,13_transformers_transformer_attention_of,1,aMjaEkkXJx,2023,The emergence of clusters in self-attention dynamics,Accept (poster),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=aMjaEkkXJx,https://www.semanticscholar.org/search?q=The+emergence+of+clusters+in+self-attention+dynamics |
| 13,13_transformers_transformer_attention_of,2,liMSqUuVg9,2023,Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection,Accept (oral),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=liMSqUuVg9,https://www.semanticscholar.org/search?q=Transformers+as+Statisticians%3A+Provable+In-Context+Learning+with+In-Context+Algorithm+Selection |
| 13,13_transformers_transformer_attention_of,3,LziniAXEI9,2023,Transformers learn to implement preconditioned gradient descent for in-context learning,Accept (poster),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=LziniAXEI9,https://www.semanticscholar.org/search?q=Transformers+learn+to+implement+preconditioned+gradient+descent+for+in-context+learning |
| 13,13_transformers_transformer_attention_of,4,p0BBKhD5aI,2024,Infinite Limits of Multi-head Transformer Dynamics,Accept (poster),6.5,0.534514616015649,1.0,https://openreview.net/forum?id=p0BBKhD5aI,https://www.semanticscholar.org/search?q=Infinite+Limits+of+Multi-head+Transformer+Dynamics |
| 13,13_transformers_transformer_attention_of,5,BtAz4a5xDg,2023,Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression,Accept (poster),6.4,0.4228600669343434,1.0,https://openreview.net/forum?id=BtAz4a5xDg,https://www.semanticscholar.org/search?q=Pretraining+task+diversity+and+the+emergence+of+non-Bayesian+in-context+learning+for+regression |
| 14,14_preference_reward_alignment_human,1,HPuSIXJaa9,2023,Direct Preference Optimization: Your Language Model is Secretly a Reward Model,Accept (oral),7.75,1.5536285105100776,1.0,https://openreview.net/forum?id=HPuSIXJaa9,https://www.semanticscholar.org/search?q=Direct+Preference+Optimization%3A+Your+Language+Model+is+Secretly+a+Reward+Model |
| 14,14_preference_reward_alignment_human,2,KwRLDkyVOl,2024,Noise Contrastive Alignment of Language Models with Explicit Rewards,Accept (poster),6.8,0.7874226403394753,1.0,https://openreview.net/forum?id=KwRLDkyVOl,https://www.semanticscholar.org/search?q=Noise+Contrastive+Alignment+of+Language+Models+with+Explicit+Rewards |
| 14,14_preference_reward_alignment_human,3,3csuL7TVpV,2024,Decoding-Time Language Model Alignment with Multiple Objectives,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=3csuL7TVpV,https://www.semanticscholar.org/search?q=Decoding-Time+Language+Model+Alignment+with+Multiple+Objectives |
| 14,14_preference_reward_alignment_human,4,Swh8LxuycA,2024,Learning Goal-Conditioned Representations for Language Reward Models,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=Swh8LxuycA,https://www.semanticscholar.org/search?q=Learning+Goal-Conditioned+Representations+for+Language+Reward+Models |
| 14,14_preference_reward_alignment_human,5,CSbGXyCswu,2023,Fine-Grained Human Feedback Gives Better Rewards for Language Model Training,Accept (spotlight),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=CSbGXyCswu,https://www.semanticscholar.org/search?q=Fine-Grained+Human+Feedback+Gives+Better+Rewards+for+Language+Model+Training |
| 15,15_pdes_pde_equations_differential,1,Aj8RKCGwjE,2024,AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=Aj8RKCGwjE,https://www.semanticscholar.org/search?q=AROMA%3A+Preserving+Spatial+Structure+for+Latent+PDE+Modeling+with+Local+Neural+Fields |
| 15,15_pdes_pde_equations_differential,2,v6YzxwJlQn,2023,Deep Equilibrium Based Neural Operators for Steady-State PDEs,Accept (poster),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=v6YzxwJlQn,https://www.semanticscholar.org/search?q=Deep+Equilibrium+Based+Neural+Operators+for+Steady-State+PDEs |
| 15,15_pdes_pde_equations_differential,3,Qv6468llWS,2023,PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers,Accept (spotlight),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=Qv6468llWS,https://www.semanticscholar.org/search?q=PDE-Refiner%3A+Achieving+Accurate+Long+Rollouts+with+Neural+PDE+Solvers |
| 15,15_pdes_pde_equations_differential,4,oUXiNX5KRm,2024,Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators,Accept (poster),6.6,0.6188172907902577,1.0,https://openreview.net/forum?id=oUXiNX5KRm,https://www.semanticscholar.org/search?q=Universal+Physics+Transformers%3A+A+Framework+For+Efficiently+Scaling+Neural+Operators |
| 15,15_pdes_pde_equations_differential,5,MtekhXRP4h,2023,Convolutional Neural Operators for robust and accurate learning of PDEs,Accept (poster),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=MtekhXRP4h,https://www.semanticscholar.org/search?q=Convolutional+Neural+Operators+for+robust+and+accurate+learning+of+PDEs |
| 16,16_the_of_deep_gradient,1,vBlzen37i0,2024,Optimal deep learning of holomorphic operators between Banach spaces,Accept (spotlight),7.666666666666667,1.5180458217194177,1.0,https://openreview.net/forum?id=vBlzen37i0,https://www.semanticscholar.org/search?q=Optimal+deep+learning+of+holomorphic+operators+between+Banach+spaces |
| 16,16_the_of_deep_gradient,2,kfdEXQu6MC,2024,A generalized neural tangent kernel for surrogate gradient learning,Accept (spotlight),7.5,1.3775413637617364,1.0,https://openreview.net/forum?id=kfdEXQu6MC,https://www.semanticscholar.org/search?q=A+generalized+neural+tangent+kernel+for+surrogate+gradient+learning |
| 16,16_the_of_deep_gradient,3,m6pVpdIN0y,2024,Neglected Hessian component explains mysteries in sharpness regularization,Accept (spotlight),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=m6pVpdIN0y,https://www.semanticscholar.org/search?q=Neglected+Hessian+component+explains+mysteries+in+sharpness+regularization |
| 16,16_the_of_deep_gradient,4,fShubymWrc,2023,Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks,Accept (spotlight),7.0,0.9254238196346696,1.0,https://openreview.net/forum?id=fShubymWrc,https://www.semanticscholar.org/search?q=Provable+Guarantees+for+Nonlinear+Feature+Learning+in+Three-Layer+Neural+Networks |
| 16,16_the_of_deep_gradient,5,konBXvt2iS,2023,Understanding Multi-phase Optimization Dynamics and Rich Nonlinear Behaviors of ReLU Networks,Accept (spotlight),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=konBXvt2iS,https://www.semanticscholar.org/search?q=Understanding+Multi-phase+Optimization+Dynamics+and+Rich+Nonlinear+Behaviors+of+ReLU+Networks |
| 17,17_audio_speech_audiovisual_generation,1,V3QZCM1AQv,2024,REBORN: Reinforcement-Learned Boundary Segmentation with Iterative Training for Unsupervised ASR,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=V3QZCM1AQv,https://www.semanticscholar.org/search?q=REBORN%3A+Reinforcement-Learned+Boundary+Segmentation+with+Iterative+Training+for+Unsupervised+ASR |
| 17,17_audio_speech_audiovisual_generation,2,18RdkSv9h9,2024,FINALLY: fast and universal speech enhancement with studio-like quality,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=18RdkSv9h9,https://www.semanticscholar.org/search?q=FINALLY%3A+fast+and+universal+speech+enhancement+with+studio-like+quality |
| 17,17_audio_speech_audiovisual_generation,3,fymr0CBDHZ,2024,SLIM: Style-Linguistics Mismatch Model for Generalized Audio Deepfake Detection,Accept (poster),6.5,0.534514616015649,1.0,https://openreview.net/forum?id=fymr0CBDHZ,https://www.semanticscholar.org/search?q=SLIM%3A+Style-Linguistics+Mismatch+Model+for+Generalized+Audio+Deepfake+Detection |
| 17,17_audio_speech_audiovisual_generation,4,IxEhb4NCvy,2024,SSDM: Scalable Speech Dysfluency Modeling,Accept (poster),6.5,0.534514616015649,1.0,https://openreview.net/forum?id=IxEhb4NCvy,https://www.semanticscholar.org/search?q=SSDM%3A+Scalable+Speech+Dysfluency+Modeling |
| 17,17_audio_speech_audiovisual_generation,5,HDVsiUHQ1w,2024,SCOREQ: Speech Quality Assessment with Contrastive Regression,Accept (poster),6.4,0.45021194124104014,1.0,https://openreview.net/forum?id=HDVsiUHQ1w,https://www.semanticscholar.org/search?q=SCOREQ%3A+Speech+Quality+Assessment+with+Contrastive+Regression |
| 18,18_optimization_convergence_gradient_convex,1,wIlmx4bHrO,2023,A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization,Accept (oral),8.0,1.7630300741352136,1.0,https://openreview.net/forum?id=wIlmx4bHrO,https://www.semanticscholar.org/search?q=A+Single-Loop+Accelerated+Extra-Gradient+Difference+Algorithm+with+Improved+Complexity+Bounds+for+Constrained+Minimax+Optimization |
| 18,18_optimization_convergence_gradient_convex,2,enlxHLwwFf,2024,Functional Bilevel Optimization for Machine Learning,Accept (spotlight),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=enlxHLwwFf,https://www.semanticscholar.org/search?q=Functional+Bilevel+Optimization+for+Machine+Learning |
| 18,18_optimization_convergence_gradient_convex,3,znY173SCxu,2023,Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value,Accept (poster),6.6,0.5903813178344521,1.0,https://openreview.net/forum?id=znY173SCxu,https://www.semanticscholar.org/search?q=Time-Reversed+Dissipation+Induces+Duality+Between+Minimizing+Gradient+Norm+and+Function+Value |
| 18,18_optimization_convergence_gradient_convex,4,aFOdln7jBV,2024,An Accelerated Gradient Method for Convex Smooth Simple Bilevel Optimization,Accept (poster),6.5,0.534514616015649,1.0,https://openreview.net/forum?id=aFOdln7jBV,https://www.semanticscholar.org/search?q=An+Accelerated+Gradient+Method+for+Convex+Smooth+Simple+Bilevel+Optimization |
| 18,18_optimization_convergence_gradient_convex,5,vIGNYQ4Alv,2023,Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization,Accept (spotlight),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=vIGNYQ4Alv,https://www.semanticscholar.org/search?q=Accelerated+Quasi-Newton+Proximal+Extragradient%3A+Faster+Rate+for+Smooth+Convex+Optimization |
| 19,19_federated_fl_clients_client,1,xW6ga9i4eA,2024,pFedClub: Controllable Heterogeneous Model Aggregation for Personalized Federated Learning,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=xW6ga9i4eA,https://www.semanticscholar.org/search?q=pFedClub%3A+Controllable+Heterogeneous+Model+Aggregation+for+Personalized+Federated+Learning |
| 19,19_federated_fl_clients_client,2,3YkeHuT1o6,2024,A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm,Accept (poster),6.666666666666667,0.6750190739733303,1.0,https://openreview.net/forum?id=3YkeHuT1o6,https://www.semanticscholar.org/search?q=A+Swiss+Army+Knife+for+Heterogeneous+Federated+Learning%3A+Flexible+Coupling+via+Trace+Norm |
| 19,19_federated_fl_clients_client,3,zpVCITHknd,2023,Towards Personalized Federated Learning via Heterogeneous Model Reassembly,Accept (poster),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=zpVCITHknd,https://www.semanticscholar.org/search?q=Towards+Personalized+Federated+Learning+via+Heterogeneous+Model+Reassembly |
| 19,19_federated_fl_clients_client,4,D6MQrw9HFu,2024,FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection,Accept (poster),6.25,0.323757929079127,1.0,https://openreview.net/forum?id=D6MQrw9HFu,https://www.semanticscholar.org/search?q=FOOGD%3A+Federated+Collaboration+for+Both+Out-of-distribution+Generalization+and+Detection |
| 19,19_federated_fl_clients_client,5,E7fZOoiEKl,2024,FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion,Accept (spotlight),6.25,0.32375792907912704,1.0,https://openreview.net/forum?id=E7fZOoiEKl,https://www.semanticscholar.org/search?q=FuseFL%3A+One-Shot+Federated+Learning+through+the+Lens+of+Causality+with+Progressive+Model+Fusion |
| 20,20_vision_tokens_and_the,1,o7DOGbZeyP,2024,LookHere: Vision Transformers with Directed Attention Generalize and Extrapolate,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=o7DOGbZeyP,https://www.semanticscholar.org/search?q=LookHere%3A+Vision+Transformers+with+Directed+Attention+Generalize+and+Extrapolate |
| 20,20_vision_tokens_and_the,2,en4LGxpd9E,2023,Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design,Accept (poster),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=en4LGxpd9E,https://www.semanticscholar.org/search?q=Getting+ViT+in+Shape%3A+Scaling+Laws+for+Compute-Optimal+Model+Design |
| 20,20_vision_tokens_and_the,3,DQgTewaKzt,2023,ZoomTrack: Target-aware Non-uniform Resizing for Efficient Visual Tracking,Accept (spotlight),6.2,0.2553388160342346,1.0,https://openreview.net/forum?id=DQgTewaKzt,https://www.semanticscholar.org/search?q=ZoomTrack%3A+Target-aware+Non-uniform+Resizing+for+Efficient+Visual+Tracking |
| 20,20_vision_tokens_and_the,4,e0SQ6wsHjv,2024,Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=e0SQ6wsHjv,https://www.semanticscholar.org/search?q=Dynamic+Tuning+Towards+Parameter+and+Inference+Efficiency+for+ViT+Adaptation |
| 20,20_vision_tokens_and_the,5,B1vGiSgELw,2024,Matryoshka Query Transformer for Large Vision-Language Models,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=B1vGiSgELw,https://www.semanticscholar.org/search?q=Matryoshka+Query+Transformer+for+Large+Vision-Language+Models |
| 21,21_video_temporal_understanding_and,1,eOonmxzzno,2024,Temporal Sentence Grounding with Relevance Feedback in Videos,Accept (poster),6.25,0.323757929079127,1.0,https://openreview.net/forum?id=eOonmxzzno,https://www.semanticscholar.org/search?q=Temporal+Sentence+Grounding+with+Relevance+Feedback+in+Videos |
| 21,21_video_temporal_understanding_and,2,PWzB2V2b6R,2024,Does Video-Text Pretraining Help Open-Vocabulary Online Action Detection?,Accept (poster),6.0,0.11300124214260512,1.0,https://openreview.net/forum?id=PWzB2V2b6R,https://www.semanticscholar.org/search?q=Does+Video-Text+Pretraining+Help+Open-Vocabulary+Online+Action+Detection%3F |
| 21,21_video_temporal_understanding_and,3,J6Niv3yrMq,2023,Glance and Focus: Memory Prompting for Multi-Event Video Question Answering,Accept (poster),5.833333333333333,-0.051783477282631406,1.0,https://openreview.net/forum?id=J6Niv3yrMq,https://www.semanticscholar.org/search?q=Glance+and+Focus%3A+Memory+Prompting+for+Multi-Event+Video+Question+Answering |
| 21,21_video_temporal_understanding_and,4,F8aSOovlEP,2024,MECD: Unlocking Multi-Event Causal Discovery in Video Reasoning,Accept (spotlight),5.75,-0.09775544479391685,1.0,https://openreview.net/forum?id=F8aSOovlEP,https://www.semanticscholar.org/search?q=MECD%3A+Unlocking+Multi-Event+Causal+Discovery+in+Video+Reasoning |
| 21,21_video_temporal_understanding_and,5,WhE4C4fLbE,2024,CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition,Accept (poster),5.5,-0.3085121317304387,1.0,https://openreview.net/forum?id=WhE4C4fLbE,https://www.semanticscholar.org/search?q=CHASE%3A+Learning+Convex+Hull+Adaptive+Shift+for+Skeleton-based+Multi-Entity+Action+Recognition |
| 22,22_attention_memory_kv_cache,1,ARAxPPIAhq,2024,xLSTM: Extended Long Short-Term Memory,Accept (spotlight),8.0,1.7990547376347805,1.0,https://openreview.net/forum?id=ARAxPPIAhq,https://www.semanticscholar.org/search?q=xLSTM%3A+Extended+Long+Short-Term+Memory |
| 22,22_attention_memory_kv_cache,2,8Ofbg2KYMu,2024,Faster Neighborhood Attention: Reducing the O(n^2) Cost of Self Attention at the Threadblock Level,Accept (poster),6.333333333333333,0.39401015805796763,1.0,https://openreview.net/forum?id=8Ofbg2KYMu,https://www.semanticscholar.org/search?q=Faster+Neighborhood+Attention%3A+Reducing+the+O%28n%5E2%29+Cost+of+Self+Attention+at+the+Threadblock+Level |
| 22,22_attention_memory_kv_cache,3,aQv5AbN1wF,2024,On Feature Learning in Structured State Space Models,Accept (poster),6.333333333333333,0.39401015805796763,1.0,https://openreview.net/forum?id=aQv5AbN1wF,https://www.semanticscholar.org/search?q=On+Feature+Learning+in+Structured+State+Space+Models |
| 22,22_attention_memory_kv_cache,4,4xDxVQHsbZ,2024,NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-add-free Attention,Accept (poster),6.25,0.32375792907912704,1.0,https://openreview.net/forum?id=4xDxVQHsbZ,https://www.semanticscholar.org/search?q=NoMAD-Attention%3A+Efficient+LLM+Inference+on+CPUs+Through+Multiply-add-free+Attention |
| 22,22_attention_memory_kv_cache,5,3SzrqwupUx,2024,Theoretical Foundations of Deep Selective State-Space Models,Accept (poster),6.25,0.32375792907912704,1.0,https://openreview.net/forum?id=3SzrqwupUx,https://www.semanticscholar.org/search?q=Theoretical+Foundations+of+Deep+Selective+State-Space+Models |
| 23,23_safety_llms_harmful_attacks,1,jXs6Cvpe7k,2024,Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks,Accept (spotlight),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=jXs6Cvpe7k,https://www.semanticscholar.org/search?q=Robust+Prompt+Optimization+for+Defending+Language+Models+Against+Jailbreaking+Attacks |
| 23,23_safety_llms_harmful_attacks,2,u9ShP64FJV,2024,Protecting Your LLMs with Information Bottleneck,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=u9ShP64FJV,https://www.semanticscholar.org/search?q=Protecting+Your+LLMs+with+Information+Bottleneck |
| 23,23_safety_llms_harmful_attacks,3,qAP6RyYIJc,2024,Stealth edits to large language models,Accept (poster),6.5,0.534514616015649,1.0,https://openreview.net/forum?id=qAP6RyYIJc,https://www.semanticscholar.org/search?q=Stealth+edits+to+large+language+models |
| 23,23_safety_llms_harmful_attacks,4,cw5mgd71jW,2024,Many-shot Jailbreaking,Accept (poster),6.4,0.45021194124104014,1.0,https://openreview.net/forum?id=cw5mgd71jW,https://www.semanticscholar.org/search?q=Many-shot+Jailbreaking |
| 23,23_safety_llms_harmful_attacks,5,1PcJ5Evta7,2024,BackdoorAlign: Mitigating Fine-tuning based Jailbreak Attack with Backdoor Enhanced Safety Alignment,Accept (poster),6.25,0.323757929079127,1.0,https://openreview.net/forum?id=1PcJ5Evta7,https://www.semanticscholar.org/search?q=BackdoorAlign%3A+Mitigating+Fine-tuning+based+Jailbreak+Attack+with+Backdoor+Enhanced+Safety+Alignment |
| 24,24_the_of_is_we,1,T0e4Nw09XX,2024,Universal Rates for Active Learning,Accept (poster),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=T0e4Nw09XX,https://www.semanticscholar.org/search?q=Universal+Rates+for+Active+Learning |
| 24,24_the_of_is_we,2,cRGINXQWem,2023,Precise asymptotic generalization for multiclass classification with overparameterized linear models,Accept (spotlight),7.333333333333333,1.2046259044681842,1.0,https://openreview.net/forum?id=cRGINXQWem,https://www.semanticscholar.org/search?q=Precise+asymptotic+generalization+for+multiclass+classification+with+overparameterized+linear+models |
| 24,24_the_of_is_we,3,7Dep87TMJs,2024,Learning with Fitzpatrick Losses,Accept (poster),6.8,0.7874226403394753,1.0,https://openreview.net/forum?id=7Dep87TMJs,https://www.semanticscholar.org/search?q=Learning+with+Fitzpatrick+Losses |
| 24,24_the_of_is_we,4,6cWDg9t3z5,2024,Universal Rates of Empirical Risk Minimization,Accept (poster),6.8,0.7874226403394753,1.0,https://openreview.net/forum?id=6cWDg9t3z5,https://www.semanticscholar.org/search?q=Universal+Rates+of+Empirical+Risk+Minimization |
| 24,24_the_of_is_we,5,4KZhZJSPYU,2023,When Does Confidence-Based Cascade Deferral Suffice?,Accept (poster),6.8,0.757902568734561,1.0,https://openreview.net/forum?id=4KZhZJSPYU,https://www.semanticscholar.org/search?q=When+Does+Confidence-Based+Cascade+Deferral+Suffice%3F |
| 25,25_games_game_equilibrium_equilibria,1,hK7XTpCtBi,2024,Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=hK7XTpCtBi,https://www.semanticscholar.org/search?q=Fast+Last-Iterate+Convergence+of+Learning+in+Games+Requires+Forgetful+Algorithms |
| 25,25_games_game_equilibrium_equilibria,2,3CtTMF5zzM,2024,On Tractable $\Phi$-Equilibria in Non-Concave Games,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=3CtTMF5zzM,https://www.semanticscholar.org/search?q=On+Tractable+%24%5CPhi%24-Equilibria+in+Non-Concave+Games |
| 25,25_games_game_equilibrium_equilibria,3,nYgs0qZJ97,2023,Regret Matching+: (In)Stability and Fast Convergence in Games,Accept (spotlight),7.0,0.9254238196346696,1.0,https://openreview.net/forum?id=nYgs0qZJ97,https://www.semanticscholar.org/search?q=Regret+Matching%2B%3A+%28In%29Stability+and+Fast+Convergence+in+Games |
| 25,25_games_game_equilibrium_equilibria,4,HW9S9vY5gZ,2024,No-regret Learning in Harmonic Games: Extrapolation in the Face of Conflicting Interests,Accept (spotlight),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=HW9S9vY5gZ,https://www.semanticscholar.org/search?q=No-regret+Learning+in+Harmonic+Games%3A+Extrapolation+in+the+Face+of+Conflicting+Interests |
| 25,25_games_game_equilibrium_equilibria,5,mZwilh3hd2,2024,Polynomial-Time Computation of Exact $\Phi$-Equilibria in Polyhedral Games,Accept (spotlight),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=mZwilh3hd2,https://www.semanticscholar.org/search?q=Polynomial-Time+Computation+of+Exact+%24%5CPhi%24-Equilibria+in+Polyhedral+Games |
| 26,26_video_motion_generation_temporal,1,VFqzxhINFU,2024,StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation,Accept (spotlight),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=VFqzxhINFU,https://www.semanticscholar.org/search?q=StoryDiffusion%3A+Consistent+Self-Attention+for+Long-Range+Image+and+Video+Generation |
| 26,26_video_motion_generation_temporal,2,YdfZP7qMzp,2024,GenRec: Unifying Video Generation and Recognition with Diffusion Models,Accept (poster),6.2,0.28160659169182256,1.0,https://openreview.net/forum?id=YdfZP7qMzp,https://www.semanticscholar.org/search?q=GenRec%3A+Unifying+Video+Generation+and+Recognition+with+Diffusion+Models |
| 26,26_video_motion_generation_temporal,3,o9Lkiv1qpc,2024,Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=o9Lkiv1qpc,https://www.semanticscholar.org/search?q=Identifying+and+Solving+Conditional+Image+Leakage+in+Image-to-Video+Diffusion+Model |
| 26,26_video_motion_generation_temporal,4,NsqxN9iOJ7,2024,Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=NsqxN9iOJ7,https://www.semanticscholar.org/search?q=Motion+Consistency+Model%3A+Accelerating+Video+Diffusion+with+Disentangled+Motion-Appearance+Distillation |
| 26,26_video_motion_generation_temporal,5,xUjBZR6b1T,2024,ReVideo: Remake a Video with Motion and Content Control,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=xUjBZR6b1T,https://www.semanticscholar.org/search?q=ReVideo%3A+Remake+a+Video+with+Motion+and+Content+Control |
| 27,27_bayesian_posterior_inference_of,1,HfQF8LoLhs,2024,Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=HfQF8LoLhs,https://www.semanticscholar.org/search?q=Asymptotics+of+Alpha-Divergence+Variational+Inference+Algorithms+with+Exponential+Families |
| 27,27_bayesian_posterior_inference_of,2,dHQ2av9NzO,2023,On the Convergence of Black-Box Variational Inference,Accept (poster),7.0,0.9254238196346697,1.0,https://openreview.net/forum?id=dHQ2av9NzO,https://www.semanticscholar.org/search?q=On+the+Convergence+of+Black-Box+Variational+Inference |
| 27,27_bayesian_posterior_inference_of,3,wLiMhVJ7fx,2023,Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability,Accept (poster),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=wLiMhVJ7fx,https://www.semanticscholar.org/search?q=Calibrating+Neural+Simulation-Based+Inference+with+Differentiable+Coverage+Probability |
| 27,27_bayesian_posterior_inference_of,4,2Cmdh5z6ph,2023,Discriminative Calibration: Check Bayesian Computation from Simulations and Flexible Classifier,Accept (poster),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=2Cmdh5z6ph,https://www.semanticscholar.org/search?q=Discriminative+Calibration%3A+Check+Bayesian+Computation+from+Simulations+and+Flexible+Classifier |
| 27,27_bayesian_posterior_inference_of,5,f71xXsoG1v,2023,Provable convergence guarantees for black-box variational inference,Accept (poster),6.6,0.5903813178344521,1.0,https://openreview.net/forum?id=f71xXsoG1v,https://www.semanticscholar.org/search?q=Provable+convergence+guarantees+for+black-box+variational+inference |
| 28,28_problems_optimization_combinatorial_search,1,sTjW3JHs2V,2023,Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets,Accept (spotlight),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=sTjW3JHs2V,https://www.semanticscholar.org/search?q=Let+the+Flows+Tell%3A++Solving+Graph+Combinatorial+Problems+with+GFlowNets |
| 28,28_problems_optimization_combinatorial_search,2,DoewNm2uT3,2024,Neural Combinatorial Optimization for Robust Routing Problem with Uncertain Travel Times,Accept (poster),6.2,0.2816065916918226,1.0,https://openreview.net/forum?id=DoewNm2uT3,https://www.semanticscholar.org/search?q=Neural+Combinatorial+Optimization+for+Robust+Routing+Problem+with+Uncertain+Travel+Times |
| 28,28_problems_optimization_combinatorial_search,3,buqvMT3B4k,2024,Self-Labeling the Job Shop Scheduling Problem,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=buqvMT3B4k,https://www.semanticscholar.org/search?q=Self-Labeling+the+Job+Shop+Scheduling+Problem |
| 28,28_problems_optimization_combinatorial_search,4,593fc38lhN,2023,Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization,Accept (poster),6.0,0.08781756513412584,1.0,https://openreview.net/forum?id=593fc38lhN,https://www.semanticscholar.org/search?q=Efficient+Meta+Neural+Heuristic+for+Multi-Objective+Combinatorial+Optimization |
| 28,28_problems_optimization_combinatorial_search,5,q1JukwH2yP,2023,Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt,Accept (poster),6.0,0.08781756513412586,1.0,https://openreview.net/forum?id=q1JukwH2yP,https://www.semanticscholar.org/search?q=Learning+to+Search+Feasible+and+Infeasible+Regions+of+Routing+Problems+with+Flexible+Neural+k-Opt |
| 29,29_matrix_the_of_is,1,ca2QmdOlIh,2023,Bayesian Extensive-Rank Matrix Factorization with Rotational Invariant Priors,Accept (spotlight),7.5,1.3442269468849417,1.0,https://openreview.net/forum?id=ca2QmdOlIh,https://www.semanticscholar.org/search?q=Bayesian+Extensive-Rank+Matrix+Factorization+with+Rotational+Invariant+Priors |
| 29,29_matrix_the_of_is,2,NgyT80IPUK,2024,Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods,Accept (poster),7.333333333333333,1.2370369058040553,1.0,https://openreview.net/forum?id=NgyT80IPUK,https://www.semanticscholar.org/search?q=Matrix+Denoising+with+Doubly+Heteroscedastic+Noise%3A+Fundamental+Limits+and+Optimal+Spectral+Methods |
| 29,29_matrix_the_of_is,3,ZGN8dOhpi6,2024,A Pairwise Pseudo-likelihood Approach for Matrix Completion with Informative Missingness,Accept (spotlight),7.0,0.9560279898886929,1.0,https://openreview.net/forum?id=ZGN8dOhpi6,https://www.semanticscholar.org/search?q=A+Pairwise+Pseudo-likelihood+Approach+for+Matrix+Completion+with+Informative+Missingness |
| 29,29_matrix_the_of_is,4,3s8V8QP9XV,2024,Nearly Optimal Approximation of Matrix Functions by the Lanczos Method,Accept (spotlight),6.8,0.7874226403394753,1.0,https://openreview.net/forum?id=3s8V8QP9XV,https://www.semanticscholar.org/search?q=Nearly+Optimal+Approximation+of+Matrix+Functions+by+the+Lanczos+Method |
| 29,29_matrix_the_of_is,5,gITGmIEinf,2024,Approximating the Top Eigenvector in Random Order Streams,Accept (spotlight),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=gITGmIEinf,https://www.semanticscholar.org/search?q=Approximating+the+Top+Eigenvector+in+Random+Order+Streams |
| 30,30_fairness_fair_groups_in,1,nzkWhoXUpv,2023,Individual Arbitrariness and Group Fairness,Accept (spotlight),7.25,1.1348253832598056,1.0,https://openreview.net/forum?id=nzkWhoXUpv,https://www.semanticscholar.org/search?q=Individual+Arbitrariness+and+Group+Fairness |
| 30,30_fairness_fair_groups_in,2,GtEmIzLZmR,2024,Achievable Fairness on Your Data With Utility Guarantees,Accept (poster),6.666666666666667,0.6750190739733303,1.0,https://openreview.net/forum?id=GtEmIzLZmR,https://www.semanticscholar.org/search?q=Achievable+Fairness+on+Your+Data+With+Utility+Guarantees |
| 30,30_fairness_fair_groups_in,3,J0Itri0UiN,2024,Counterfactual Fairness by Combining Factual and Counterfactual Predictions,Accept (poster),6.333333333333333,0.39401015805796763,1.0,https://openreview.net/forum?id=J0Itri0UiN,https://www.semanticscholar.org/search?q=Counterfactual+Fairness+by+Combining+Factual+and+Counterfactual+Predictions |
| 30,30_fairness_fair_groups_in,4,ylceJ2xIw5,2024,Fair Wasserstein Coresets,Accept (poster),6.25,0.32375792907912704,1.0,https://openreview.net/forum?id=ylceJ2xIw5,https://www.semanticscholar.org/search?q=Fair+Wasserstein+Coresets |
| 30,30_fairness_fair_groups_in,5,wwkQUiaKbo,2023,Adapting Fairness Interventions to Missing Values,Accept (poster),6.2,0.25533881603423464,1.0,https://openreview.net/forum?id=wwkQUiaKbo,https://www.semanticscholar.org/search?q=Adapting+Fairness+Interventions+to+Missing+Values |
| 31,31_label_labels_the_noisy,1,AqcPvWwktK,2024,Semi-supervised Multi-label Learning with Balanced Binary Angular Margin Loss,Accept (spotlight),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=AqcPvWwktK,https://www.semanticscholar.org/search?q=Semi-supervised+Multi-label+Learning+with+Balanced+Binary+Angular+Margin+Loss |
| 31,31_label_labels_the_noisy,2,4RoD1o7yq6,2023,Binary Classification with Confidence Difference,Accept (poster),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=4RoD1o7yq6,https://www.semanticscholar.org/search?q=Binary+Classification+with+Confidence+Difference |
| 31,31_label_labels_the_noisy,3,JpqEzPTuv6,2024,What Makes Partial-Label Learning Algorithms Effective?,Accept (poster),6.4,0.45021194124104014,1.0,https://openreview.net/forum?id=JpqEzPTuv6,https://www.semanticscholar.org/search?q=What+Makes+Partial-Label+Learning+Algorithms+Effective%3F |
| 31,31_label_labels_the_noisy,4,2NKumsITFw,2024,Learning from Noisy Labels via Conditional Distributionally Robust Optimization,Accept (poster),6.333333333333333,0.39401015805796763,1.0,https://openreview.net/forum?id=2NKumsITFw,https://www.semanticscholar.org/search?q=Learning+from+Noisy+Labels+via+Conditional+Distributionally+Robust+Optimization |
| 31,31_label_labels_the_noisy,5,wnPlJNiqfA,2024,KFNN: K-Free Nearest Neighbor For Crowdsourcing,Accept (poster),6.25,0.32375792907912704,1.0,https://openreview.net/forum?id=wnPlJNiqfA,https://www.semanticscholar.org/search?q=KFNN%3A+K-Free+Nearest+Neighbor+For+Crowdsourcing |
| 32,32_continual_forgetting_knowledge_unlearning,1,opaRhDvQRD,2024,"Forgetting, Ignorance or Myopia: Revisiting Key Challenges in Online Continual Learning",Accept (poster),7.0,0.9560279898886926,1.0,https://openreview.net/forum?id=opaRhDvQRD,https://www.semanticscholar.org/search?q=Forgetting%2C+Ignorance+or+Myopia%3A+Revisiting+Key+Challenges+in+Online+Continual+Learning |
| 32,32_continual_forgetting_knowledge_unlearning,2,P6aJ7BqYlc,2024,GACL: Exemplar-Free Generalized Analytic Continual Learning,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=P6aJ7BqYlc,https://www.semanticscholar.org/search?q=GACL%3A+Exemplar-Free+Generalized+Analytic+Continual+Learning |
| 32,32_continual_forgetting_knowledge_unlearning,3,9XieH21Tlf,2023,Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality,Accept (spotlight),6.4,0.4228600669343434,1.0,https://openreview.net/forum?id=9XieH21Tlf,https://www.semanticscholar.org/search?q=Hierarchical+Decomposition+of+Prompt-Based+Continual+Learning%3A+Rethinking+Obscured+Sub-optimality |
| 32,32_continual_forgetting_knowledge_unlearning,4,TZ5k9IYBBf,2024,RanDumb: Random Representations Outperform Online Continually Learned Representations,Accept (poster),6.25,0.32375792907912704,1.0,https://openreview.net/forum?id=TZ5k9IYBBf,https://www.semanticscholar.org/search?q=RanDumb%3A+Random+Representations+Outperform+Online+Continually+Learned+Representations |
| 32,32_continual_forgetting_knowledge_unlearning,5,LswqtKU9op,2023,Prompt-augmented Temporal Point Process for Streaming Event Sequence,Accept (poster),6.25,0.2972191287592618,1.0,https://openreview.net/forum?id=LswqtKU9op,https://www.semanticscholar.org/search?q=Prompt-augmented+Temporal+Point+Process+for+Streaming+Event+Sequence |
| 33,33_knowledge_retrieval_rag_query,1,S1fc92uemC,2024,RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs,Accept (poster),7.0,0.9560279898886926,1.0,https://openreview.net/forum?id=S1fc92uemC,https://www.semanticscholar.org/search?q=RankRAG%3A+Unifying+Context+Ranking+with+Retrieval-Augmented+Generation+in+LLMs |
| 33,33_knowledge_retrieval_rag_query,2,bkUvKPKafQ,2024,ChatQA: Surpassing GPT-4 on Conversational QA and RAG,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=bkUvKPKafQ,https://www.semanticscholar.org/search?q=ChatQA%3A+Surpassing+GPT-4+on+Conversational+QA+and+RAG |
| 33,33_knowledge_retrieval_rag_query,3,VQyb9LKmUH,2024,A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning,Accept (poster),6.666666666666667,0.6750190739733303,1.0,https://openreview.net/forum?id=VQyb9LKmUH,https://www.semanticscholar.org/search?q=A+Prompt-Based+Knowledge+Graph+Foundation+Model+for+Universal+In-Context+Reasoning |
| 33,33_knowledge_retrieval_rag_query,4,BpJ6OTfWw3,2024,Clustering then Propagation: Select Better Anchors for Knowledge Graph Embedding,Accept (poster),6.5,0.534514616015649,1.0,https://openreview.net/forum?id=BpJ6OTfWw3,https://www.semanticscholar.org/search?q=Clustering+then+Propagation%3A+Select+Better+Anchors+for+Knowledge+Graph+Embedding |
| 33,33_knowledge_retrieval_rag_query,5,hkujvAPVsg,2024,HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models,Accept (poster),6.333333333333333,0.39401015805796763,1.0,https://openreview.net/forum?id=hkujvAPVsg,https://www.semanticscholar.org/search?q=HippoRAG%3A+Neurobiologically+Inspired+Long-Term+Memory+for+Large+Language+Models |
| 34,34_communication_distributed_federated_convergence,1,IUKff7nYmW,2024,Lower Bounds and Optimal Algorithms for Non-Smooth Convex Decentralized Optimization over Time-Varying Networks,Accept (poster),7.25,1.1667846768252146,1.0,https://openreview.net/forum?id=IUKff7nYmW,https://www.semanticscholar.org/search?q=Lower+Bounds+and+Optimal+Algorithms+for+Non-Smooth+Convex+Decentralized+Optimization+over+Time-Varying+Networks |
| 34,34_communication_distributed_federated_convergence,2,WukSyFSzDt,2024,Stabilized Proximal-Point Methods for Federated Optimization,Accept (spotlight),6.8,0.7874226403394753,1.0,https://openreview.net/forum?id=WukSyFSzDt,https://www.semanticscholar.org/search?q=Stabilized+Proximal-Point+Methods+for+Federated+Optimization |
| 34,34_communication_distributed_federated_convergence,3,uaNZvF1VFe,2024,Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=uaNZvF1VFe,https://www.semanticscholar.org/search?q=Efficient+Sign-Based+Optimization%3A+Accelerating+Convergence+via+Variance+Reduction |
| 34,34_communication_distributed_federated_convergence,4,MirclT6zpv,2023,Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization,Accept (poster),6.4,0.4228600669343434,1.0,https://openreview.net/forum?id=MirclT6zpv,https://www.semanticscholar.org/search?q=Delayed+Algorithms+for+Distributed+Stochastic+Weakly+Convex+Optimization |
| 34,34_communication_distributed_federated_convergence,5,HeJ1cBAgiV,2024,SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning,Accept (poster),6.333333333333333,0.39401015805796763,1.0,https://openreview.net/forum?id=HeJ1cBAgiV,https://www.semanticscholar.org/search?q=SCAFFLSA%3A+Taming+Heterogeneity+in+Federated+Linear+Stochastic+Approximation+and+TD+Learning |
| 35,35_medical_segmentation_clinical_images,1,105ZuvpdyW,2024,SegVol: Universal and Interactive Volumetric Medical Image Segmentation,Accept (spotlight),7.666666666666667,1.5180458217194177,1.0,https://openreview.net/forum?id=105ZuvpdyW,https://www.semanticscholar.org/search?q=SegVol%3A+Universal+and+Interactive+Volumetric+Medical+Image+Segmentation |
| 35,35_medical_segmentation_clinical_images,2,xE7oH5iVGK,2023,LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching,Accept (poster),7.0,0.9254238196346696,1.0,https://openreview.net/forum?id=xE7oH5iVGK,https://www.semanticscholar.org/search?q=LVM-Med%3A+Learning+Large-Scale+Self-Supervised+Vision+Models+for+Medical+Imaging+via+Second-order+Graph+Matching |
| 35,35_medical_segmentation_clinical_images,3,qlnlamFQEa,2023,Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback,Accept (spotlight),6.8,0.757902568734561,1.0,https://openreview.net/forum?id=qlnlamFQEa,https://www.semanticscholar.org/search?q=Aligning+Synthetic+Medical+Images+with+Clinical+Knowledge+using+Human+Feedback |
| 35,35_medical_segmentation_clinical_images,4,STrpbhrvt3,2024,A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis,Accept (spotlight),6.5,0.534514616015649,1.0,https://openreview.net/forum?id=STrpbhrvt3,https://www.semanticscholar.org/search?q=A+Textbook+Remedy+for+Domain+Shifts%3A+Knowledge+Priors+for+Medical+Image+Analysis |
| 35,35_medical_segmentation_clinical_images,5,Xp8qhdmeb4,2024,E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation,Accept (poster),6.0,0.11300124214260514,1.0,https://openreview.net/forum?id=Xp8qhdmeb4,https://www.semanticscholar.org/search?q=E2ENet%3A+Dynamic+Sparse+Feature+Fusion+for+Accurate+and+Efficient+3D+Medical+Image+Segmentation |
| 36,36_agents_llms_agent_language,1,dG1HwKMYbC,2024,FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making,Accept (poster),6.666666666666667,0.67501907397333,1.0,https://openreview.net/forum?id=dG1HwKMYbC,https://www.semanticscholar.org/search?q=FinCon%3A+A+Synthesized+LLM+Multi-Agent+System+with+Conceptual+Verbal+Reinforcement+for+Enhanced+Financial+Decision+Making |
| 36,36_agents_llms_agent_language,2,jU9qiRMDtR,2023,SPRING: Studying Papers and Reasoning to play Games,Accept (poster),6.5,0.5066206923843977,1.0,https://openreview.net/forum?id=jU9qiRMDtR,https://www.semanticscholar.org/search?q=SPRING%3A+Studying+Papers+and+Reasoning+to+play+Games |
| 36,36_agents_llms_agent_language,3,kEPpD7yETM,2024,Large Language Models Play StarCraft II:Benchmarks and A Chain of Summarization Approach,Accept (poster),6.333333333333333,0.39401015805796763,1.0,https://openreview.net/forum?id=kEPpD7yETM,https://www.semanticscholar.org/search?q=Large+Language+Models+Play+StarCraft+II%3ABenchmarks+and+A+Chain+of+Summarization+Approach |
| 36,36_agents_llms_agent_language,4,DRC9pZwBwR,2024,Recursive Introspection: Teaching Language Model Agents How to Self-Improve,Accept (poster),6.333333333333333,0.39401015805796763,1.0,https://openreview.net/forum?id=DRC9pZwBwR,https://www.semanticscholar.org/search?q=Recursive+Introspection%3A+Teaching+Language+Model+Agents+How+to+Self-Improve |
| 36,36_agents_llms_agent_language,5,vAElhFcKW6,2023,Reflexion: language agents with verbal reinforcement learning,Accept (poster),6.2,0.25533881603423464,1.0,https://openreview.net/forum?id=vAElhFcKW6,https://www.semanticscholar.org/search?q=Reflexion%3A+language+agents+with+verbal+reinforcement+learning |
| 37,37_lora_finetuning_lowrank_adaptation,1,6ZBHIEtdP4,2024,PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models,Accept (spotlight),7.5,1.3775413637617366,1.0,https://openreview.net/forum?id=6ZBHIEtdP4,https://www.semanticscholar.org/search?q=PiSSA%3A+Principal+Singular+Values+and+Singular+Vectors+Adaptation+of+Large+Language+Models |
| 37,37_lora_finetuning_lowrank_adaptation,2,kuCY0mW4Q3,2024,VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=kuCY0mW4Q3,https://www.semanticscholar.org/search?q=VB-LoRA%3A+Extreme+Parameter+Efficient+Fine-Tuning+with+Vector+Banks |
| 37,37_lora_finetuning_lowrank_adaptation,3,L8ifDX5XNq,2024,LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning,Accept (poster),6.333333333333333,0.39401015805796763,1.0,https://openreview.net/forum?id=L8ifDX5XNq,https://www.semanticscholar.org/search?q=LISA%3A+Layerwise+Importance+Sampling+for+Memory-Efficient+Large+Language+Model+Fine-Tuning |
| 37,37_lora_finetuning_lowrank_adaptation,4,VaLAWrLHJv,2024,LoRA-GA: Low-Rank Adaptation with Gradient Approximation,Accept (poster),6.0,0.11300124214260514,1.0,https://openreview.net/forum?id=VaLAWrLHJv,https://www.semanticscholar.org/search?q=LoRA-GA%3A+Low-Rank+Adaptation+with+Gradient+Approximation |
| 37,37_lora_finetuning_lowrank_adaptation,5,sn3UrYRItk,2024,The Impact of Initialization on LoRA Finetuning Dynamics,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=sn3UrYRItk,https://www.semanticscholar.org/search?q=The+Impact+of+Initialization+on+LoRA+Finetuning+Dynamics |
| 38,38_watermarking_watermark_watermarks_image,1,7hy5fy2OC6,2024,Invisible Image Watermarks Are Provably Removable Using Generative AI,Accept (poster),7.0,0.9560279898886929,1.0,https://openreview.net/forum?id=7hy5fy2OC6,https://www.semanticscholar.org/search?q=Invisible+Image+Watermarks+Are+Provably+Removable+Using+Generative+AI |
| 38,38_watermarking_watermark_watermarks_image,2,FZ45kf5pIA,2024,Edit Distance Robust Watermarks via Indexing Pseudorandom Codes,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=FZ45kf5pIA,https://www.semanticscholar.org/search?q=Edit+Distance+Robust+Watermarks+via+Indexing+Pseudorandom+Codes |
| 38,38_watermarking_watermark_watermarks_image,3,6YKMBUiIsG,2024,Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=6YKMBUiIsG,https://www.semanticscholar.org/search?q=Inevitable+Trade-off+between+Watermark+Strength+and+Speculative+Sampling+Efficiency+for+Language+Models |
| 38,38_watermarking_watermark_watermarks_image,4,HjeKHxK2VH,2024,WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=HjeKHxK2VH,https://www.semanticscholar.org/search?q=WaterMax%3A+breaking+the+LLM+watermark+detectability-robustness-quality+trade-off |
| 38,38_watermarking_watermark_watermarks_image,5,RvoxlFvnlX,2024,ROBIN: Robust and Invisible Watermarks for Diffusion Models with Adversarial Optimization,Accept (poster),6.25,0.32375792907912704,1.0,https://openreview.net/forum?id=RvoxlFvnlX,https://www.semanticscholar.org/search?q=ROBIN%3A+Robust+and+Invisible+Watermarks+for+Diffusion+Models+with+Adversarial+Optimization |
| 39,39_clustering_algorithm_algorithms_approximation,1,MFWgLCWgUB,2023,Random Cuts are Optimal for Explainable k-Medians,Accept (oral),8.0,1.7630300741352134,1.0,https://openreview.net/forum?id=MFWgLCWgUB,https://www.semanticscholar.org/search?q=Random+Cuts+are+Optimal+for+Explainable+k-Medians |
| 39,39_clustering_algorithm_algorithms_approximation,2,lgtsXxk4dF,2024,Clustering with Non-adaptive Subset Queries,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=lgtsXxk4dF,https://www.semanticscholar.org/search?q=Clustering+with+Non-adaptive+Subset+Queries |
| 39,39_clustering_algorithm_algorithms_approximation,3,5VE1iLeYOz,2024,Efficient Centroid-Linkage Clustering,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=5VE1iLeYOz,https://www.semanticscholar.org/search?q=Efficient+Centroid-Linkage+Clustering |
| 39,39_clustering_algorithm_algorithms_approximation,4,Actjv6Wect,2024,Proportional Fairness in Non-Centroid Clustering,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=Actjv6Wect,https://www.semanticscholar.org/search?q=Proportional+Fairness+in+Non-Centroid+Clustering |
| 39,39_clustering_algorithm_algorithms_approximation,5,8XRMbNAP6Z,2023,Near-Optimal $k$-Clustering in the Sliding Window Model,Accept (poster),7.0,0.9254238196346697,1.0,https://openreview.net/forum?id=8XRMbNAP6Z,https://www.semanticscholar.org/search?q=Near-Optimal+%24k%24-Clustering+in+the+Sliding+Window+Model |
| 40,40_anomaly_detection_anomalies_normal,1,8VKxTlnejE,2024,MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection,Accept (poster),6.25,0.323757929079127,1.0,https://openreview.net/forum?id=8VKxTlnejE,https://www.semanticscholar.org/search?q=MambaAD%3A+Exploring+State+Space+Models+for+Multi-class+Unsupervised+Anomaly+Detection |
| 40,40_anomaly_detection_anomalies_normal,2,zNiJZUAlxg,2024,ResAD: A Simple Framework for Class Generalizable Anomaly Detection,Accept (spotlight),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=zNiJZUAlxg,https://www.semanticscholar.org/search?q=ResAD%3A+A+Simple+Framework+for+Class+Generalizable+Anomaly+Detection |
| 40,40_anomaly_detection_anomalies_normal,3,aW5bSuduF1,2023,Drift doesn't Matter: Dynamic Decomposition with Diffusion Reconstruction for Unstable Multivariate Time Series Anomaly Detection,Accept (poster),6.0,0.08781756513412588,1.0,https://openreview.net/forum?id=aW5bSuduF1,https://www.semanticscholar.org/search?q=Drift+doesn%27t+Matter%3A+Dynamic+Decomposition+with+Diffusion+Reconstruction+for+Unstable+Multivariate+Time+Series+Anomaly+Detection |
| 40,40_anomaly_detection_anomalies_normal,4,gmf5Aj01Hz,2024,SARAD: Spatial Association-Aware Anomaly Detection and Diagnosis for Multivariate Time Series,Accept (poster),5.75,-0.09775544479391682,1.0,https://openreview.net/forum?id=gmf5Aj01Hz,https://www.semanticscholar.org/search?q=SARAD%3A+Spatial+Association-Aware+Anomaly+Detection+and+Diagnosis+for+Multivariate+Time+Series |
| 40,40_anomaly_detection_anomalies_normal,5,UFW67uduJd,2023,MEMTO: Memory-guided Transformer for Multivariate Time Series Anomaly Detection,Accept (poster),5.75,-0.12158399849101006,1.0,https://openreview.net/forum?id=UFW67uduJd,https://www.semanticscholar.org/search?q=MEMTO%3A+Memory-guided+Transformer+for+Multivariate+Time+Series+Anomaly+Detection |
| 41,41_equivariant_symmetries_group_symmetry,1,L86glqNCUj,2024,Symmetries in Overparametrized Neural Networks: A Mean Field View,Accept (spotlight),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=L86glqNCUj,https://www.semanticscholar.org/search?q=Symmetries+in+Overparametrized+Neural+Networks%3A+A+Mean+Field+View |
| 41,41_equivariant_symmetries_group_symmetry,2,bNIHdyunFC,2023,Learning Layer-wise Equivariances Automatically using Gradients,Accept (spotlight),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=bNIHdyunFC,https://www.semanticscholar.org/search?q=Learning+Layer-wise+Equivariances+Automatically+using+Gradients |
| 41,41_equivariant_symmetries_group_symmetry,3,8lbFwpebeu,2023,Investigating how ReLU-networks encode symmetries,Accept (poster),6.6,0.5903813178344521,1.0,https://openreview.net/forum?id=8lbFwpebeu,https://www.semanticscholar.org/search?q=Investigating+how+ReLU-networks+encode+symmetries |
| 41,41_equivariant_symmetries_group_symmetry,4,DnO6LTQ77U,2023,Approximation-Generalization Trade-offs under (Approximate) Group Equivariance,Accept (poster),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=DnO6LTQ77U,https://www.semanticscholar.org/search?q=Approximation-Generalization+Trade-offs+under+%28Approximate%29+Group+Equivariance |
| 41,41_equivariant_symmetries_group_symmetry,5,2FMJtNDLeE,2023,"A General Theory of Correct, Incorrect, and Extrinsic Equivariance",Accept (poster),6.333333333333333,0.3670196499676404,1.0,https://openreview.net/forum?id=2FMJtNDLeE,https://www.semanticscholar.org/search?q=A+General+Theory+of+Correct%2C+Incorrect%2C+and+Extrinsic+Equivariance |
| 42,42_backdoor_attacks_attack_defense,1,Kl13lipxTW,2024,BackTime: Backdoor Attacks on Multivariate Time Series Forecasting,Accept (spotlight),7.0,0.9560279898886929,1.0,https://openreview.net/forum?id=Kl13lipxTW,https://www.semanticscholar.org/search?q=BackTime%3A+Backdoor+Attacks+on+Multivariate+Time+Series+Forecasting |
| 42,42_backdoor_attacks_attack_defense,2,VFhN15Vlkj,2023,Neural Polarizer: A Lightweight and Effective Backdoor Defense via Purifying Poisoned Features,Accept (poster),6.25,0.2972191287592618,1.0,https://openreview.net/forum?id=VFhN15Vlkj,https://www.semanticscholar.org/search?q=Neural+Polarizer%3A+A+Lightweight+and+Effective+Backdoor+Defense+via+Purifying+Poisoned+Features |
| 42,42_backdoor_attacks_attack_defense,3,Y6RV6z98Pk,2024,SampDetox: Black-box Backdoor Defense via Perturbation-based Sample Detoxification,Accept (poster),6.2,0.28160659169182267,1.0,https://openreview.net/forum?id=Y6RV6z98Pk,https://www.semanticscholar.org/search?q=SampDetox%3A+Black-box+Backdoor+Defense+via+Perturbation-based+Sample+Detoxification |
| 42,42_backdoor_attacks_attack_defense,4,H1CQZqpgdQ,2023,CBD: A Certified Backdoor Detector Based on Local Dominant Probability,Accept (poster),6.2,0.2553388160342346,1.0,https://openreview.net/forum?id=H1CQZqpgdQ,https://www.semanticscholar.org/search?q=CBD%3A+A+Certified+Backdoor+Detector+Based+on+Local+Dominant+Probability |
| 42,42_backdoor_attacks_attack_defense,5,KyVBzkConO,2024,Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=KyVBzkConO,https://www.semanticscholar.org/search?q=Injecting+Undetectable+Backdoors+in+Obfuscated+Neural+Networks+and+Language+Models |
| 43,43_ood_detection_outofdistribution_id,1,VLQYtVMTYz,2024,Energy-based Hopfield Boosting for Out-of-Distribution Detection,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=VLQYtVMTYz,https://www.semanticscholar.org/search?q=Energy-based+Hopfield+Boosting+for+Out-of-Distribution+Detection |
| 43,43_ood_detection_outofdistribution_id,2,OtU6VvXJue,2023,Learning to Augment Distributions for Out-of-distribution Detection,Accept (poster),6.75,0.7160222560095337,1.0,https://openreview.net/forum?id=OtU6VvXJue,https://www.semanticscholar.org/search?q=Learning+to+Augment+Distributions+for+Out-of-distribution+Detection |
| 43,43_ood_detection_outofdistribution_id,3,A5pabdZp2F,2024,MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities,Accept (spotlight),6.666666666666667,0.6750190739733303,1.0,https://openreview.net/forum?id=A5pabdZp2F,https://www.semanticscholar.org/search?q=MultiOOD%3A+Scaling+Out-of-Distribution+Detection+for+Multiple+Modalities |
| 43,43_ood_detection_outofdistribution_id,4,A86JTXllHa,2023,On the Importance of Feature Separability in Predicting Out-Of-Distribution Error,Accept (poster),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=A86JTXllHa,https://www.semanticscholar.org/search?q=On+the+Importance+of+Feature+Separability+in+Predicting+Out-Of-Distribution+Error |
| 43,43_ood_detection_outofdistribution_id,5,HZQZli6amV,2023,ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets,Accept (spotlight),6.4,0.4228600669343434,1.0,https://openreview.net/forum?id=HZQZli6amV,https://www.semanticscholar.org/search?q=ID+and+OOD+Performance+Are+Sometimes+Inversely+Correlated+on+Real-world+Datasets |
| 44,44_conformal_prediction_coverage_sets,1,kkmPe0rzY1,2024,Robust Conformal Prediction Using Privileged Information,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=kkmPe0rzY1,https://www.semanticscholar.org/search?q=Robust+Conformal+Prediction+Using+Privileged+Information |
| 44,44_conformal_prediction_coverage_sets,2,YI4bn6aAmz,2023,Conformal Prediction Sets for Ordinal Classification,Accept (poster),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=YI4bn6aAmz,https://www.semanticscholar.org/search?q=Conformal+Prediction+Sets+for+Ordinal+Classification |
| 44,44_conformal_prediction_coverage_sets,3,eP6cDDwBNC,2023,TRIAGE: Characterizing and auditing training data for improved regression,Accept (poster),6.4,0.4228600669343434,1.0,https://openreview.net/forum?id=eP6cDDwBNC,https://www.semanticscholar.org/search?q=TRIAGE%3A+Characterizing+and+auditing+training+data+for+improved+regression |
| 44,44_conformal_prediction_coverage_sets,4,KNZYJ5zQsG,2024,Generalized Fast Exact Conformalization,Accept (poster),6.2,0.28160659169182267,1.0,https://openreview.net/forum?id=KNZYJ5zQsG,https://www.semanticscholar.org/search?q=Generalized+Fast+Exact+Conformalization |
| 44,44_conformal_prediction_coverage_sets,5,gKLgY3m9zj,2024,An Information Theoretic Perspective on Conformal Prediction,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=gKLgY3m9zj,https://www.semanticscholar.org/search?q=An+Information+Theoretic+Perspective+on+Conformal+Prediction |
| 45,45_recommendation_user_recommender_item,1,xojbzSYIVS,2024,LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation,Accept (spotlight),6.666666666666667,0.6750190739733303,1.0,https://openreview.net/forum?id=xojbzSYIVS,https://www.semanticscholar.org/search?q=LLM-ESR%3A+Large+Language+Models+Enhancement+for+Long-tailed+Sequential+Recommendation |
| 45,45_recommendation_user_recommender_item,2,h3BdT2UMWQ,2024,Breaking Determinism: Fuzzy Modeling of Sequential Recommendation Using Discrete State Space Diffusion Model,Accept (poster),6.25,0.323757929079127,1.0,https://openreview.net/forum?id=h3BdT2UMWQ,https://www.semanticscholar.org/search?q=Breaking+Determinism%3A+Fuzzy+Modeling+of+Sequential+Recommendation+Using+Discrete+State+Space+Diffusion+Model |
| 45,45_recommendation_user_recommender_item,3,JyWAFGCJPl,2024,Fine Tuning Out-of-Vocabulary Item Recommendation with User Sequence Imagination,Accept (spotlight),6.25,0.32375792907912704,1.0,https://openreview.net/forum?id=JyWAFGCJPl,https://www.semanticscholar.org/search?q=Fine+Tuning+Out-of-Vocabulary+Item+Recommendation+with+User+Sequence+Imagination |
| 45,45_recommendation_user_recommender_item,4,mHsxsrLl0y,2023,Theoretically Guaranteed Bidirectional Data Rectification for Robust Sequential Recommendation,Accept (poster),6.2,0.2553388160342346,1.0,https://openreview.net/forum?id=mHsxsrLl0y,https://www.semanticscholar.org/search?q=Theoretically+Guaranteed+Bidirectional+Data+Rectification+for+Robust+Sequential+Recommendation |
| 45,45_recommendation_user_recommender_item,5,Px1hQM72iX,2024,Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval,Accept (poster),6.0,0.11300124214260507,1.0,https://openreview.net/forum?id=Px1hQM72iX,https://www.semanticscholar.org/search?q=Density-based+User+Representation+using+Gaussian+Process+Regression+for+Multi-interest+Personalized+Retrieval |
| 46,46_language_llms_of_the,1,0NMzBwqaAJ,2024,Not All Tokens Are What You Need for Pretraining,Accept (oral),7.666666666666667,1.518045821719418,1.0,https://openreview.net/forum?id=0NMzBwqaAJ,https://www.semanticscholar.org/search?q=Not+All+Tokens+Are+What+You+Need+for+Pretraining |
| 46,46_language_llms_of_the,2,pASJxzMJb7,2024,Zipfian Whitening,Accept (poster),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=pASJxzMJb7,https://www.semanticscholar.org/search?q=Zipfian+Whitening |
| 46,46_language_llms_of_the,3,RwBObRsIzC,2024,Zero-Shot Tokenizer Transfer,Accept (poster),6.666666666666667,0.6750190739733303,1.0,https://openreview.net/forum?id=RwBObRsIzC,https://www.semanticscholar.org/search?q=Zero-Shot+Tokenizer+Transfer |
| 46,46_language_llms_of_the,4,CEk6JK71Mb,2023,Meet in the Middle: A New Pre-training Paradigm,Accept (poster),6.6,0.5903813178344521,1.0,https://openreview.net/forum?id=CEk6JK71Mb,https://www.semanticscholar.org/search?q=Meet+in+the+Middle%3A+A+New+Pre-training+Paradigm |
| 46,46_language_llms_of_the,5,KEe4IUp20I,2024,SpaceByte: Towards Deleting Tokenization from Large Language Modeling,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=KEe4IUp20I,https://www.semanticscholar.org/search?q=SpaceByte%3A+Towards+Deleting+Tokenization+from+Large+Language+Modeling |
| 47,47_quantum_classical_of_the,1,WTLvXdzhmP,2024,Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm,Accept (spotlight),7.2,1.1246333394379104,1.0,https://openreview.net/forum?id=WTLvXdzhmP,https://www.semanticscholar.org/search?q=Statistical+Estimation+in+the+Spiked+Tensor+Model+via+the+Quantum+Approximate+Optimization+Algorithm |
| 47,47_quantum_classical_of_the,2,XCkII8nCt3,2024,Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits,Accept (spotlight),7.0,0.9560279898886928,1.0,https://openreview.net/forum?id=XCkII8nCt3,https://www.semanticscholar.org/search?q=Non-asymptotic+Approximation+Error+Bounds+of+Parameterized+Quantum+Circuits |
| 47,47_quantum_classical_of_the,3,6gcY0MGNhj,2023,Statistical Analysis of Quantum State Learning Process in Quantum Neural Networks,Accept (poster),6.8,0.7579025687345609,1.0,https://openreview.net/forum?id=6gcY0MGNhj,https://www.semanticscholar.org/search?q=Statistical+Analysis+of+Quantum+State+Learning+Process+in+Quantum+Neural+Networks |
| 47,47_quantum_classical_of_the,4,4aIpgq1nuI,2023,What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement.,Accept (spotlight),6.6,0.5903813178344521,1.0,https://openreview.net/forum?id=4aIpgq1nuI,https://www.semanticscholar.org/search?q=What+Makes+Data+Suitable+for+a+Locally+Connected+Neural+Network%3F+A+Necessary+and+Sufficient+Condition+Based+on+Quantum+Entanglement. |
| 47,47_quantum_classical_of_the,5,IKQOS8rqwr,2023,QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning,Accept (spotlight),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=IKQOS8rqwr,https://www.semanticscholar.org/search?q=QuACK%3A+Accelerating+Gradient-Based+Quantum+Optimization+with+Koopman+Operator+Learning |
| 48,48_pruning_sparsity_compression_sparse,1,Llu9nJal7b,2024,MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models,Accept (spotlight),7.5,1.3775413637617366,1.0,https://openreview.net/forum?id=Llu9nJal7b,https://www.semanticscholar.org/search?q=MaskLLM%3A+Learnable+Semi-Structured+Sparsity+for+Large+Language+Models |
| 48,48_pruning_sparsity_compression_sparse,2,9U0nLnNMJ7,2024,Compact Language Models via Pruning and Knowledge Distillation,Accept (poster),7.0,0.9560279898886929,1.0,https://openreview.net/forum?id=9U0nLnNMJ7,https://www.semanticscholar.org/search?q=Compact+Language+Models+via+Pruning+and+Knowledge+Distillation |
| 48,48_pruning_sparsity_compression_sparse,3,RwK0tgfptL,2024,Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=RwK0tgfptL,https://www.semanticscholar.org/search?q=Shaving+Weights+with+Occam%27s+Razor%3A+Bayesian+Sparsification+for+Neural+Networks+using+the+Marginal+Likelihood |
| 48,48_pruning_sparsity_compression_sparse,4,ktpG37Dzh5,2024,BMRS: Bayesian Model Reduction for Structured Pruning,Accept (spotlight),6.333333333333333,0.39401015805796763,1.0,https://openreview.net/forum?id=ktpG37Dzh5,https://www.semanticscholar.org/search?q=BMRS%3A+Bayesian+Model+Reduction+for+Structured+Pruning |
| 48,48_pruning_sparsity_compression_sparse,5,Jup0qZxH7U,2024,Adaptive Layer Sparsity for Large Language Models via Activation Correlation Assessment,Accept (poster),6.25,0.323757929079127,1.0,https://openreview.net/forum?id=Jup0qZxH7U,https://www.semanticscholar.org/search?q=Adaptive+Layer+Sparsity+for+Large+Language+Models+via+Activation+Correlation+Assessment |
| 49,49_hallucination_hallucinations_lvlms_decoding,1,NrwASKGm7A,2024,ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models,Accept (poster),6.25,0.323757929079127,1.0,https://openreview.net/forum?id=NrwASKGm7A,https://www.semanticscholar.org/search?q=ANAH-v2%3A+Scaling+Analytical+Hallucination+Annotation+of+Large+Language+Models |
| 49,49_hallucination_hallucinations_lvlms_decoding,2,9GhSOp1LYH,2024,Leveraging Hallucinations to Reduce Manual Prompt Dependency in Promptable Segmentation,Accept (poster),6.25,0.32375792907912704,1.0,https://openreview.net/forum?id=9GhSOp1LYH,https://www.semanticscholar.org/search?q=Leveraging+Hallucinations+to+Reduce+Manual+Prompt+Dependency+in+Promptable+Segmentation |
| 49,49_hallucination_hallucinations_lvlms_decoding,3,KNrwaFEi1u,2024,Multi-Object Hallucination in Vision Language Models,Accept (poster),6.0,0.11300124214260511,1.0,https://openreview.net/forum?id=KNrwaFEi1u,https://www.semanticscholar.org/search?q=Multi-Object+Hallucination+in+Vision+Language+Models |
| 49,49_hallucination_hallucinations_lvlms_decoding,4,yQL5tutdaH,2024,"Toward a Stable, Fair, and Comprehensive Evaluation of Object Hallucination in Large Vision-Language Models",Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=yQL5tutdaH,https://www.semanticscholar.org/search?q=Toward+a+Stable%2C+Fair%2C+and+Comprehensive+Evaluation+of+Object+Hallucination+in+Large+Vision-Language+Models |
| 49,49_hallucination_hallucinations_lvlms_decoding,5,SF2GlFhVsS,2024,Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization,Accept (poster),5.75,-0.09775544479391676,1.0,https://openreview.net/forum?id=SF2GlFhVsS,https://www.semanticscholar.org/search?q=Alleviating+Hallucinations+in+Large+Vision-Language+Models+through+Hallucination-Induced+Optimization |
| 50,50_quantization_quantized_lowbit_4bit,1,mp8u2Pcmqz,2024,DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs,Accept (oral),7.6,1.4618440385363454,1.0,https://openreview.net/forum?id=mp8u2Pcmqz,https://www.semanticscholar.org/search?q=DuQuant%3A+Distributing+Outliers+via+Dual+Transformation+Makes+Stronger+Quantized+LLMs |
| 50,50_quantization_quantized_lowbit_4bit,2,EfpZNpkrm2,2024,QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation,Accept (poster),7.25,1.1667846768252146,1.0,https://openreview.net/forum?id=EfpZNpkrm2,https://www.semanticscholar.org/search?q=QuanTA%3A+Efficient+High-Rank+Fine-Tuning+of+LLMs+with+Quantum-Informed+Tensor+Adaptation |
| 50,50_quantization_quantized_lowbit_4bit,3,dfqsW38v1X,2024,QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs,Accept (poster),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=dfqsW38v1X,https://www.semanticscholar.org/search?q=QuaRot%3A+Outlier-Free+4-Bit+Inference+in+Rotated+LLMs |
| 50,50_quantization_quantized_lowbit_4bit,4,UARTFgkTqW,2024,MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=UARTFgkTqW,https://www.semanticscholar.org/search?q=MagR%3A+Weight+Magnitude+Reduction+for+Enhancing+Post-Training+Quantization |
| 50,50_quantization_quantized_lowbit_4bit,5,xrk9g5vcXR,2023,QuIP: 2-Bit Quantization of Large Language Models With Guarantees,Accept (spotlight),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=xrk9g5vcXR,https://www.semanticscholar.org/search?q=QuIP%3A+2-Bit+Quantization+of+Large+Language+Models+With+Guarantees |
| 51,51_optimization_bayesian_bo_the,1,9KtX12YmA7,2023,The Behavior and Convergence of Local Bayesian Optimization,Accept (spotlight),7.5,1.3442269468849415,1.0,https://openreview.net/forum?id=9KtX12YmA7,https://www.semanticscholar.org/search?q=The+Behavior+and+Convergence+of+Local+Bayesian+Optimization |
| 51,51_optimization_bayesian_bo_the,2,1vyAG6j9PE,2023,Unexpected Improvements to Expected Improvement for Bayesian Optimization,Accept (spotlight),7.25,1.1348253832598056,1.0,https://openreview.net/forum?id=1vyAG6j9PE,https://www.semanticscholar.org/search?q=Unexpected+Improvements+to+Expected+Improvement+for+Bayesian+Optimization |
| 51,51_optimization_bayesian_bo_the,3,TVD3wNVH9A,2023,Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces,Accept (poster),6.8,0.757902568734561,1.0,https://openreview.net/forum?id=TVD3wNVH9A,https://www.semanticscholar.org/search?q=Bounce%3A+Reliable+High-Dimensional+Bayesian+Optimization+for+Combinatorial+and+Mixed+Spaces |
| 51,51_optimization_bayesian_bo_the,4,T5UfIfmDbq,2024,Monte Carlo Tree Search based Space Transfer for Black Box Optimization,Accept (spotlight),6.75,0.7452713029521708,1.0,https://openreview.net/forum?id=T5UfIfmDbq,https://www.semanticscholar.org/search?q=Monte+Carlo+Tree+Search+based+Space+Transfer+for+Black+Box+Optimization |
| 51,51_optimization_bayesian_bo_the,5,da0ZJatRCN,2024,Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=da0ZJatRCN,https://www.semanticscholar.org/search?q=Active+Learning+for+Derivative-Based+Global+Sensitivity+Analysis+with+Gaussian+Processes |
| 52,52_ssl_selfsupervised_unlabeled_semisupervised,1,dlCTmEyq6y,2024,Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data,Accept (spotlight),7.25,1.1667846768252146,1.0,https://openreview.net/forum?id=dlCTmEyq6y,https://www.semanticscholar.org/search?q=Semi-Supervised+Sparse+Gaussian+Classification%3A+Provable+Benefits+of+Unlabeled+Data |
| 52,52_ssl_selfsupervised_unlabeled_semisupervised,2,Z8TjsPFBSx,2023,Characterizing the Impacts of Semi-supervised Learning for Weak Supervision,Accept (poster),6.6,0.5903813178344521,1.0,https://openreview.net/forum?id=Z8TjsPFBSx,https://www.semanticscholar.org/search?q=Characterizing+the+Impacts+of+Semi-supervised+Learning+for+Weak+Supervision |
| 52,52_ssl_selfsupervised_unlabeled_semisupervised,3,utreNaM1VY,2023,Can semi-supervised learning use all the data effectively? A lower bound perspective,Accept (spotlight),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=utreNaM1VY,https://www.semanticscholar.org/search?q=Can+semi-supervised+learning+use+all+the+data+effectively%3F+A+lower+bound+perspective |
| 52,52_ssl_selfsupervised_unlabeled_semisupervised,4,geLARFEK8O,2023,Combating Representation Learning Disparity with Geometric Harmonization,Accept (spotlight),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=geLARFEK8O,https://www.semanticscholar.org/search?q=Combating+Representation+Learning+Disparity+with+Geometric+Harmonization |
| 52,52_ssl_selfsupervised_unlabeled_semisupervised,5,lkBygTc0SI,2023,Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning,Accept (poster),6.5,0.5066206923843978,1.0,https://openreview.net/forum?id=lkBygTc0SI,https://www.semanticscholar.org/search?q=Do+SSL+Models+Have+D%C3%A9j%C3%A0+Vu%3F+A+Case+of+Unintended+Memorization+in+Self-supervised+Learning |
| 53,53_manipulation_dexterous_grasp_contact,1,Glt37xoU7e,2024,Omnigrasp: Grasping Diverse Objects with Simulated Humanoids,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=Glt37xoU7e,https://www.semanticscholar.org/search?q=Omnigrasp%3A+Grasping+Diverse+Objects+with+Simulated+Humanoids |
| 53,53_manipulation_dexterous_grasp_contact,2,ecRaDicXxw,2023,DiffVL: Scaling Up Soft Body Manipulation using Vision-Language Driven Differentiable Physics,Accept (poster),6.0,0.08781756513412584,1.0,https://openreview.net/forum?id=ecRaDicXxw,https://www.semanticscholar.org/search?q=DiffVL%3A+Scaling+Up+Soft+Body+Manipulation+using+Vision-Language+Driven+Differentiable+Physics |
| 53,53_manipulation_dexterous_grasp_contact,3,fwvfxDbUFw,2023,Learning Score-based Grasping Primitive for Human-assisting Dexterous Grasping,Accept (poster),6.0,0.08781756513412586,1.0,https://openreview.net/forum?id=fwvfxDbUFw,https://www.semanticscholar.org/search?q=Learning+Score-based+Grasping+Primitive+for+Human-assisting+Dexterous+Grasping |
| 53,53_manipulation_dexterous_grasp_contact,4,QeWibaTmnn,2024,Grasp as You Say: Language-guided Dexterous Grasp Generation,Accept (poster),5.75,-0.09775544479391682,1.0,https://openreview.net/forum?id=QeWibaTmnn,https://www.semanticscholar.org/search?q=Grasp+as+You+Say%3A+Language-guided+Dexterous+Grasp+Generation |
| 53,53_manipulation_dexterous_grasp_contact,5,6FYh6gxzPf,2024,Active Perception for Grasp Detection via Neural Graspness Field,Accept (poster),5.5,-0.30851213173043873,1.0,https://openreview.net/forum?id=6FYh6gxzPf,https://www.semanticscholar.org/search?q=Active+Perception+for+Grasp+Detection+via+Neural+Graspness+Field |
| 54,54_decoding_speculative_draft_inference,1,8iPobEKUUA,2024,Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=8iPobEKUUA,https://www.semanticscholar.org/search?q=Efficient+Minimum+Bayes+Risk+Decoding+using+Low-Rank+Matrix+Completion+Algorithms |
| 54,54_decoding_speculative_draft_inference,2,rk2L9YGDi2,2024,Sequoia: Scalable and Robust Speculative Decoding,Accept (spotlight),6.5,0.534514616015649,1.0,https://openreview.net/forum?id=rk2L9YGDi2,https://www.semanticscholar.org/search?q=Sequoia%3A+Scalable+and+Robust+Speculative+Decoding |
| 54,54_decoding_speculative_draft_inference,3,5G7ve8E1Lu,2024,Grammar-Aligned Decoding,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=5G7ve8E1Lu,https://www.semanticscholar.org/search?q=Grammar-Aligned+Decoding |
| 54,54_decoding_speculative_draft_inference,4,Ni9kebsSTt,2024,Nearest Neighbor Speculative Decoding for LLM Generation and Attribution,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=Ni9kebsSTt,https://www.semanticscholar.org/search?q=Nearest+Neighbor+Speculative+Decoding+for+LLM+Generation+and+Attribution |
| 54,54_decoding_speculative_draft_inference,5,dLnduWGTB4,2024,QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=dLnduWGTB4,https://www.semanticscholar.org/search?q=QUEST%3A+Quality-Aware+Metropolis-Hastings+Sampling+for+Machine+Translation |
| 55,55_face_facial_identity_deepfake,1,FNzpVTpNbN,2024,DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable Diffusion,Accept (poster),6.5,0.5345146160156489,1.0,https://openreview.net/forum?id=FNzpVTpNbN,https://www.semanticscholar.org/search?q=DiffusionFake%3A+Enhancing+Generalization+in+Deepfake+Detection+via+Guided+Stable+Diffusion |
| 55,55_face_facial_identity_deepfake,2,4bJufOS6No,2024,On Learning Multi-Modal Forgery Representation for Diffusion Generated Video Detection,Accept (poster),6.2,0.28160659169182267,1.0,https://openreview.net/forum?id=4bJufOS6No,https://www.semanticscholar.org/search?q=On+Learning+Multi-Modal+Forgery+Representation+for+Diffusion+Generated+Video+Detection |
| 55,55_face_facial_identity_deepfake,3,X2UMdvcmMo,2024,FuseAnyPart: Diffusion-Driven Facial Parts Swapping via Multiple Reference Images,Accept (spotlight),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=X2UMdvcmMo,https://www.semanticscholar.org/search?q=FuseAnyPart%3A+Diffusion-Driven+Facial+Parts+Swapping+via+Multiple+Reference+Images |
| 55,55_face_facial_identity_deepfake,4,KKrj1vCQaG,2024,RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance,Accept (poster),6.0,0.1130012421426051,1.0,https://openreview.net/forum?id=KKrj1vCQaG,https://www.semanticscholar.org/search?q=RectifID%3A+Personalizing+Rectified+Flow+with+Anchored+Classifier+Guidance |
| 55,55_face_facial_identity_deepfake,5,OGQWZ3p0Zn,2023,Inserting Anybody in Diffusion Models via Celeb Basis,Accept (poster),6.0,0.08781756513412586,1.0,https://openreview.net/forum?id=OGQWZ3p0Zn,https://www.semanticscholar.org/search?q=Inserting+Anybody+in+Diffusion+Models+via+Celeb+Basis |
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