Most Cited ICLR "market interference" Papers
6,124 papers found • Page 23 of 31
Conference
Aligned Datasets Improve Detection of Latent Diffusion-Generated Images
Anirudh Sundara Rajan, Utkarsh Ojha, Jedidiah Schloesser et al.
ImagenHub: Standardizing the evaluation of conditional image generation models
Max Ku, Tianle Li, Kai Zhang et al.
MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?
YiFan Zhang, Huanyu Zhang, Haochen Tian et al.
Learning Energy Decompositions for Partial Inference in GFlowNets
Hyosoon Jang, Minsu Kim, Sungsoo Ahn
MuPT: A Generative Symbolic Music Pretrained Transformer
Xingwei Qu, yuelin bai, Yinghao MA et al.
Order-aware Interactive Segmentation
Bin Wang, Anwesa Choudhuri, Meng Zheng et al.
Discovering Temporally Compositional Neural Manifolds with Switching Infinite GPFA
Changmin Yu, Maneesh Sahani, Máté Lengyel
ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models
Seonghwan Park, Jaehyeon Jeong, Yongjun Kim et al.
SOHES: Self-supervised Open-world Hierarchical Entity Segmentation
Shengcao Cao, Jiuxiang Gu, Jason Kuen et al.
Sharpness-Aware Minimization Efficiently Selects Flatter Minima Late In Training
Zhanpeng Zhou, Mingze Wang, Yuchen Mao et al.
Matryoshka Diffusion Models
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang et al.
Data-independent Module-aware Pruning for Hierarchical Vision Transformers
Yang He, Joey Tianyi Zhou
PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training
Dawei Zhu, Nan Yang, Liang Wang et al.
ImDy: Human Inverse Dynamics from Imitated Observations
Xinpeng Liu, Junxuan Liang, Zili Lin et al.
PRIME: Prioritizing Interpretability in Failure Mode Extraction
Keivan Rezaei, Mehrdad Saberi, Mazda Moayeri et al.
Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks
Binghui Li, Zhixuan Pan, Kaifeng Lyu et al.
Analysis of Linear Mode Connectivity via Permutation-Based Weight Matching: With Insights into Other Permutation Search Methods
Akira Ito, Masanori Yamada, Atsutoshi Kumagai
Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation
Satoki Ishikawa, Rio Yokota, Ryo Karakida
Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting
Melanie Sclar, Yejin Choi, Yulia Tsvetkov et al.
High Fidelity Neural Audio Compression
Yossi Adi, Gabriel Synnaeve, Jade Copet et al.
Controlled Text Generation via Language Model Arithmetic
Jasper Dekoninck, Marc Fischer, Luca Beurer-Kellner et al.
Social-Transmotion: Promptable Human Trajectory Prediction
Saeed Saadatnejad, Yang Gao, Kaouther Messaoud et al.
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
Defu Cao, Furong Jia, Sercan Arik et al.
Determine-Then-Ensemble: Necessity of Top-k Union for Large Language Model Ensembling
Yuxuan YAO, Han Wu, Mingyang LIU et al.
CABINET: Content Relevance-based Noise Reduction for Table Question Answering
Sohan Patnaik, Heril Changwal, Milan Aggarwal et al.
State Space Model Meets Transformer: A New Paradigm for 3D Object Detection
Chuxin Wang, Wenfei Yang, Xiang Liu et al.
Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making
Jeonghye Kim, Su Young Lee, Woojun Kim et al.
A primer on analytical learning dynamics of nonlinear neural networks
Rodrigo Carrasco-Davis, Erin Grant
AmortizedPeriod: Attention-based Amortized Inference for Periodicity Identification
Hang Yu, Cong Liao, Ruolan Liu et al.
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation
Noel Loo, Ramin Hasani, Mathias Lechner et al.
Timer-XL: Long-Context Transformers for Unified Time Series Forecasting
Yong Liu, Guo Qin, Xiangdong Huang et al.
Neural Fluid Simulation on Geometric Surfaces
Haoxiang Wang, Tao Yu, Hui Qiao et al.
Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning
Li Ren, Chen Chen, Liqiang Wang et al.
PWM: Policy Learning with Multi-Task World Models
Ignat Georgiev, Varun Giridhar, Nick Hansen et al.
Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders
Hien Dang, Tho-Huu Tran, Tan Nguyen et al.
LILO: Learning Interpretable Libraries by Compressing and Documenting Code
Gabriel Grand, Lio Wong, Maddy Bowers et al.
Adaptive $Q$-Network: On-the-fly Target Selection for Deep Reinforcement Learning
Théo Vincent, Fabian Wahren, Jan Peters et al.
Do Contemporary Causal Inference Models Capture Real-World Heterogeneity? Findings from a Large-Scale Benchmark
Haining Yu, Yizhou Sun
Improved algorithm and bounds for successive projection
Jiashun Jin, Tracy Ke, Gabriel Moryoussef et al.
Point-based Instance Completion with Scene Constraints
Wesley Khademi, Li Fuxin
Spectral Compressive Imaging via Unmixing-driven Subspace Diffusion Refinement
Haijin Zeng, Benteng Sun, Yongyong Chen et al.
Unifying Causal Representation Learning with the Invariance Principle
Dingling Yao, Dario Rancati, Riccardo Cadei et al.
Deep Signature: Characterization of Large-Scale Molecular Dynamics
Tiexin Qin, Mengxu ZHU, Chunyang Li et al.
TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks
Haiyan Jiang, Vincent Zoonekynd, Giulia De Masi et al.
InstaSHAP: Interpretable Additive Models Explain Shapley Values Instantly
James Enouen, Yan Liu
LLaMA-Adapter: Efficient Fine-tuning of Large Language Models with Zero-initialized Attention
Renrui Zhang, Jiaming Han, Chris Liu et al.
DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness
Shoumik Saha, Wenxiao Wang, Yigitcan Kaya et al.
LLMs' Potential Influences on Our Democracy: Challenges and Opportunities
Yujin Potter, David Rand, Yejin Choi et al.
Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods
Yuto Nishimura, Taiji Suzuki
Exploring Diffusion Time-steps for Unsupervised Representation Learning
Zhongqi Yue, Zhongqi Yue, Jiankun Wang et al.
Fine-Tuning Language Models for Factuality
Katherine Tian, Eric Mitchell, Huaxiu Yao et al.
Masked Completion via Structured Diffusion with White-Box Transformers
Druv Pai, Sam Buchanan, Ziyang Wu et al.
Solving hidden monotone variational inequalities with surrogate losses
Ryan D'Orazio, Danilo Vucetic, Zichu Liu et al.
Neural Common Neighbor with Completion for Link Prediction
Xiyuan Wang, Haotong Yang, Muhan Zhang
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos
Dayal Singh Kalra, Tianyu He, Maissam Barkeshli
Mayfly: a Neural Data Structure for Graph Stream Summarization
yuan feng, Yukun Cao, Hairu Wang et al.
DOS: Diverse Outlier Sampling for Out-of-Distribution Detection
Wenyu Jiang, Hao Cheng, MingCai Chen et al.
Dynamic Low-Rank Sparse Adaptation for Large Language Models
Weizhong Huang, Yuxin Zhang, Xiawu Zheng et al.
3D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation
Chen Zhao, Tong Zhang, Mathieu Salzmann
Synaptic Weight Distributions Depend on the Geometry of Plasticity
Roman Pogodin, Jonathan Cornford, Arna Ghosh et al.
Identifiability for Gaussian Processes with Holomorphic Kernels
Ameer Qaqish, Didong Li
Enhancing Human-AI Collaboration Through Logic-Guided Reasoning
Chengzhi Cao, Yinghao Fu, Sheng Xu et al.
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform Generation
Roi Benita, Michael Elad, Joseph Keshet
Exploring Effective Stimulus Encoding via Vision System Modeling for Visual Prostheses
Chuanqing Wang, Di Wu, Chaoming Fang et al.
Communication-Efficient Federated Non-Linear Bandit Optimization
Chuanhao Li, Chong Liu, Yu-Xiang Wang
Is Your Video Language Model a Reliable Judge?
Ming Liu, Wensheng Zhang
OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text
Keiran Paster, Marco Dos Santos, Zhangir Azerbayev et al.
Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization
Hamidreza Almasi, Harsh Mishra, Balajee Vamanan et al.
Param$\Delta$ for Direct Mixing: Post-Train Large Language Model At Zero Cost
Sheng Cao, Mingrui Wu, Karthik Prasad et al.
Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces
Andy (DiJia) Su, Sainbayar Sukhbaatar, Michael Rabbat et al.
CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repair
Mingjie Liu, Yun-Da Tsai, Wenfei Zhou et al.
Latent Bayesian Optimization via Autoregressive Normalizing Flows
Seunghun Lee, Jinyoung Park, Jaewon Chu et al.
Tuning Frequency Bias of State Space Models
Annan Yu, Dongwei Lyu, Soon Hoe Lim et al.
Interpreting the Second-Order Effects of Neurons in CLIP
Yossi Gandelsman, Alexei Efros, Jacob Steinhardt
Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations
Nick Jiang, Anish Kachinthaya, Suzanne Petryk et al.
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time
Dennis Frauen, Konstantin Hess, Stefan Feuerriegel
GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries
Xiaoqi Wang, Han Wei Shen
Robust Classification via Regression for Learning with Noisy Labels
Erik Englesson, Hossein Azizpour
Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning
Amrith Setlur, Chirag Nagpal, Adam Fisch et al.
Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition
Jean-Rémy Conti, Stephan CLEMENCON
ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models
İlker Kesen, Andrea Pedrotti, Mustafa Dogan et al.
Heterogeneous Personalized Federated Learning by Local-Global Updates Mixing via Convergence Rate
Meirui Jiang, Anjie Le, Xiaoxiao Li et al.
Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning
Hyungho Na, Yunkyeong Seo, Il-chul Moon
Addressing Signal Delay in Deep Reinforcement Learning
Wei Wang, Dongqi Han, Xufang Luo et al.
Invariance-based Learning of Latent Dynamics
Kai Lagemann, Christian Lagemann, Sach Mukherjee
Learning in reverse causal strategic environments with ramifications on two sided markets
Seamus Somerstep, Yuekai Sun, Yaacov Ritov
Decoupling regularization from the action space
Sobhan Mohammadpour, Emma Frejinger, Pierre-Luc Bacon
Zero-shot Model-based Reinforcement Learning using Large Language Models
Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat et al.
Sufficient Context: A New Lens on Retrieval Augmented Generation Systems
Hailey Joren, Jianyi Zhang, Chun-Sung Ferng et al.
A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization
Kim Youwang, Lee Hyun, Kim Sung-Bin et al.
Semantic Aware Representation Learning for Lifelong Learning
Fahad Sarfraz, Elahe Arani, Bahram Zonooz
Detecting Backdoor Samples in Contrastive Language Image Pretraining
Hanxun Huang, Sarah Erfani, Yige Li et al.
The Value of Sensory Information to a Robot
Arjun Krishna, Edward Hu, Dinesh Jayaraman
Layer-wise linear mode connectivity
Linara Adilova, Maksym Andriushchenko, Michael Kamp et al.
Training Diffusion Models with Reinforcement Learning
Kevin Black, Michael Janner, Yilun Du et al.
Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks
Vaidehi Ramesh Patil, Peter Hase, Mohit Bansal
metabench - A Sparse Benchmark of Reasoning and Knowledge in Large Language Models
Alex Kipnis, Konstantinos Voudouris, Luca Schulze Buschoff et al.
Gradual Domain Adaptation via Gradient Flow
Zhan ZHUANG, Yu Zhang, Ying Wei
On the Parameterization of Second-Order Optimization Effective towards the Infinite Width
Satoki Ishikawa, Ryo Karakida
MixSATGEN: Learning Graph Mixing for SAT Instance Generation
Xinyan Chen, Yang Li, Runzhong Wang et al.
Revolutionizing EMCCD Denoising through a Novel Physics-Based Learning Framework for Noise Modeling
Haiyang Jiang, Tetsuichi Wazawa, Imari Sato et al.
Memory Efficient Transformer Adapter for Dense Predictions
Dong Zhang, Rui Yan, Pingcheng Dong et al.
Motif: Intrinsic Motivation from Artificial Intelligence Feedback
Martin Klissarov, Pierluca D'Oro, Shagun Sodhani et al.
Multi-task Learning with 3D-Aware Regularization
Wei-Hong Li, Steven McDonagh, Ales Leonardis et al.
DiffPuter: Empowering Diffusion Models for Missing Data Imputation
Hengrui Zhang, Liancheng Fang, Qitian Wu et al.
Generating Likely Counterfactuals Using Sum-Product Networks
Jiří Němeček, Tomáš Pevný, Jakub Marecek
Tag2Text: Guiding Vision-Language Model via Image Tagging
Xinyu Huang, Youcai Zhang, Jinyu Ma et al.
The Foundations of Tokenization: Statistical and Computational Concerns
Juan Luis Gastaldi, John Terilla, Luca Malagutti et al.
Efficient Heterogeneous Meta-Learning via Channel Shuffling Modulation
Minh Hoang, Carl Kingsford
A General Framework for Off-Policy Learning with Partially-Observed Reward
Rikiya Takehi, Masahiro Asami, Kosuke Kawakami et al.
GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs
Pengcheng Jiang, Cao Xiao, Adam Cross et al.
VDT: General-purpose Video Diffusion Transformers via Mask Modeling
Haoyu Lu, Guoxing Yang, Nanyi Fei et al.
Rethinking Graph Prompts: Unraveling the Power of Data Manipulation in Graph Neural Networks
Chenyi Zi, Bowen LIU, Xiangguo SUN et al.
Joint Fine-tuning and Conversion of Pretrained Speech and Language Models towards Linear Complexity
Mutian He, Philip N. Garner
Divide and not forget: Ensemble of selectively trained experts in Continual Learning
Grzegorz Rypeść, Sebastian Cygert, Valeriya Khan et al.
Neural Wave Equation for Irregularly Sampled Sequence Data
Arkaprava Majumdar, M Anand Krishna, P. K. Srijith
Understanding Long Videos with Multimodal Language Models
Kanchana Ranasinghe, Xiang Li, Kumara Kahatapitiya et al.
EControl: Fast Distributed Optimization with Compression and Error Control
Yuan Gao, Rustem Islamov, Sebastian Stich
Protecting against simultaneous data poisoning attacks
Neel Alex, Muhammad Shoaib Ahmed Siddiqui, Amartya Sanyal et al.
Rethinking Reward Modeling in Preference-based Large Language Model Alignment
Hao Sun, Yunyi Shen, Jean-Francois Ton
Accurate Forgetting for Heterogeneous Federated Continual Learning
Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang et al.
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
Ming Jin, Shiyu Wang, Lintao Ma et al.
Query-Policy Misalignment in Preference-Based Reinforcement Learning
Xiao Hu, Jianxiong Li, Xianyuan Zhan et al.
CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents
Siyuan Qi, Shuo Chen, Yexin Li et al.
Time Travel in LLMs: Tracing Data Contamination in Large Language Models
Shahriar Golchin, Mihai Surdeanu
X-ALMA: Plug & Play Modules and Adaptive Rejection for Quality Translation at Scale
Haoran Xu, Kenton Murray, Philipp Koehn et al.
Semantix: An Energy-guided Sampler for Semantic Style Transfer
Huiang He, Minghui HU, Chuanxia Zheng et al.
Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation
Luca Eyring, Dominik Klein, Théo Uscidda et al.
Efficient Off-Policy Learning for High-Dimensional Action Spaces
Fabian Otto, Philipp Becker, Vien A Ngo et al.
RandLoRA: Full rank parameter-efficient fine-tuning of large models
Paul Albert, Frederic Zhang, Hemanth Saratchandran et al.
Tangent Transformers for Composition,Privacy and Removal
Tian Yu Liu, Aditya Golatkar, Stefano Soatto
Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
Yuhan Chen, Yihong Luo, Yifan Song et al.
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View
HAOYUE DAI, Ignavier Ng, Gongxu Luo et al.
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory
Francesco Mori, Stefano Sarao Mannelli, Francesca Mignacco
Scalable and Effective Implicit Graph Neural Networks on Large Graphs
Juncheng Liu, Bryan Hooi, Kenji Kawaguchi et al.
Machine Unlearning for Image-to-Image Generative Models
Guihong Li, Hsiang Hsu, Chun-Fu Chen et al.
Emu: Generative Pretraining in Multimodality
Quan Sun, Qiying Yu, Yufeng Cui et al.
CONGO: Compressive Online Gradient Optimization
Jeremy Carleton, Prathik Vijaykumar, Divyanshu Saxena et al.
Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning
Shuo He, Chaojie Wang, Guowu Yang et al.
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Sebastian Pineda Arango, Fabio Ferreira, Arlind Kadra et al.
ToVE: Efficient Vision-Language Learning via Knowledge Transfer from Vision Experts
Yuanchen Wu, Junlong Du, Ke Yan et al.
GTMGC: Using Graph Transformer to Predict Molecule’s Ground-State Conformation
Guikun Xu, Yongquan Jiang, PengChuan Lei et al.
Edge-aware Image Smoothing with Relative Wavelet Domain Representation
Huiqing Qi, Xiaoliu Luo, Tingting Li et al.
When does compositional structure yield compositional generalization? A kernel theory.
Samuel Lippl, Kimberly Stachenfeld
Learning Nash Equilibria in Rank-1 Games
Nikolas Patris, Ioannis Panageas
TVNet: A Novel Time Series Analysis Method Based on Dynamic Convolution and 3D-Variation
Chenghan Li, Mingchen LI, Ruisheng Diao
RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Parth Sarthi, Salman Abdullah, Aditi Tuli et al.
Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning
Congpei Qiu, Tong Zhang, Yanhao Wu et al.
Provable unlearning in topic modeling and downstream tasks
Stanley Wei, Sadhika Malladi, Sanjeev Arora et al.
Object-Centric Pretraining via Target Encoder Bootstrapping
Nikola Đukić, Tim Lebailly, Tinne Tuytelaars
Efficient ConvBN Blocks for Transfer Learning and Beyond
Kaichao You, Guo Qin, Anchang Bao et al.
LASeR: Towards Diversified and Generalizable Robot Design with Large Language Models
JUNRU SONG, Yang Yang, Huan Xiao et al.
Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models
Fei Shen, Hu Ye, Jun Zhang et al.
Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models
Senmao Li, Joost van de Weijer, taihang Hu et al.
Conformal Language Modeling
Victor Quach, Adam Fisch, Tal Schuster et al.
Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning
Antoine Bambade, Fabian Schramm, Adrien Taylor et al.
Efficient Backpropagation with Variance Controlled Adaptive Sampling
Ziteng Wang, Jianfei Chen, Jun Zhu
PiCO: Peer Review in LLMs based on Consistency Optimization
Kun-Peng Ning, Shuo Yang, Yuyang Liu et al.
Most discriminative stimuli for functional cell type clustering
Max F. Burg, Thomas Zenkel, Michaela Vystrčilová et al.
Can We Ignore Labels in Out of Distribution Detection?
Hong Yang, Qi Yu, Travis Desell
Fast, Expressive $\mathrm{SE}(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space
Erik Bekkers, Sharvaree Vadgama, Rob Hesselink et al.
SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels
Xiangyu Dong, Xingyi Zhang, Lei Chen et al.
ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
Pengwei Tang, Xiaolin Hu, Yong Liu
AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning
Rohan Sharma, Kaiyi Ji, Zhiqiang Xu et al.
Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation
Kim Yong Tan, YUEMING LYU, Ivor Tsang et al.
Making Retrieval-Augmented Language Models Robust to Irrelevant Context
Ori Yoran, Tomer Wolfson, Ori Ram et al.
Diffusion Model for Dense Matching
Jisu Nam, Gyuseong Lee, Seonwoo Kim et al.
Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation
Wenxuan Zhang, Youssef Mohamed, Bernard Ghanem et al.
Competitive Fair Scheduling with Predictions
Tianming Zhao, Chunqiu xia, Xiaomin Chang et al.
Circumventing Concept Erasure Methods For Text-To-Image Generative Models
Minh Pham, Kelly Marshall, Niv Cohen et al.
Meta-Learning Priors Using Unrolled Proximal Networks
Yilang Zhang, Georgios B Giannakis
DyST: Towards Dynamic Neural Scene Representations on Real-World Videos
Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf et al.
Online-to-Offline RL for Agent Alignment
Xu Liu, Haobo Fu, Stefano V. Albrecht et al.
BECLR: Batch Enhanced Contrastive Few-Shot Learning
Stylianos Poulakakis-Daktylidis, Hadi Jamali-Rad
Accelerated Sampling with Stacked Restricted Boltzmann Machines
Jorge Fernandez-de-Cossio-Diaz, Clément Roussel, Simona Cocco et al.
Facing the Elephant in the Room: Visual Prompt Tuning or Full finetuning?
Cheng Han, Qifan Wang, Yiming Cui et al.
On the Benefits of Memory for Modeling Time-Dependent PDEs
Ricardo Buitrago Ruiz, Tanya Marwah, Albert Gu et al.
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis
DIPANJYOTI PAUL, Arpita Chowdhury, Xinqi Xiong et al.
The Case for Cleaner Biosignals: High-fidelity Neural Compressor Enables Transfer from Cleaner iEEG to Noisier EEG
Francesco Carzaniga, Gary Hoppeler, Michael Hersche et al.
Do LLMs have Consistent Values?
Naama Rozen, Liat Bezalel, Gal Elidan et al.
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems
Dan MacKinlay, Russell Tsuchida, Daniel Pagendam et al.
Adaptive Transformer Programs: Bridging the Gap Between Performance and Interpretability in Transformers
Quoc-Vinh Lai-Dang, Taemin Kang, Seungah Son
A Causal Lens for Learning Long-term Fair Policies
Jacob Lear, Lu Zhang
The Generalization Gap in Offline Reinforcement Learning
Ishita Mediratta, Qingfei You, Minqi Jiang et al.
ComaDICE: Offline Cooperative Multi-Agent Reinforcement Learning with Stationary Distribution Shift Regularization
The Viet Bui, Thanh Nguyen, Tien Mai
ControlAR: Controllable Image Generation with Autoregressive Models
Zongming Li, Tianheng Cheng, Shoufa Chen et al.
Fat-to-Thin Policy Optimization: Offline Reinforcement Learning with Sparse Policies
Lingwei Zhu, Han Wang, Yukie Nagai
Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning
Finn Rietz, Erik Schaffernicht, Stefan Heinrich et al.
Mind the Gap: Examining the Self-Improvement Capabilities of Large Language Models
Yuda Song, Hanlin Zhang, Carson Eisenach et al.
State Representation Learning Using an Unbalanced Atlas
Li Meng, Morten Goodwin, Anis Yazidi et al.
Latent 3D Graph Diffusion
Yuning You, Ruida Zhou, Jiwoong Park et al.
RetroInText: A Multimodal Large Language Model Enhanced Framework for Retrosynthetic Planning via In-Context Representation Learning
Chenglong Kang, Xiaoyi Liu, Fei Guo
PhyloLM: Inferring the Phylogeny of Large Language Models and Predicting their Performances in Benchmarks
Nicolas Yax, Pierre-Yves Oudeyer, Stefano Palminteri
Improving Text-to-Image Consistency via Automatic Prompt Optimization
Melissa Hall, Michal Drozdzal, Oscar Mañas et al.
OvercookedV2: Rethinking Overcooked for Zero-Shot Coordination
Tobias Gessler, Tin Dizdarevic, Ani Calinescu et al.
Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting
Enyi Jiang, Yibo Jacky Zhang, Sanmi Koyejo
Tool-Augmented Reward Modeling
Lei Li, Yekun Chai, Shuohuan Wang et al.
Score-based free-form architectures for high-dimensional Fokker-Planck equations
Feng Liu, Faguo Wu, Xiao Zhang
ACTIVE: Offline Reinforcement Learning via Adaptive Imitation and In-sample $V$-Ensemble
Tianyuan Chen, Ronglong Cai, Faguo Wu et al.
Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling
Aadirupa Saha, Branislav Kveton