ICLR Papers
6,124 papers found • Page 91 of 123
Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Models
Tianjian Li, Haoran Xu, Philipp Koehn et al.
Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step Reasoning
Yiwei Li, Peiwen Yuan, Shaoxiong Feng et al.
Estimating Conditional Mutual Information for Dynamic Feature Selection
Soham Gadgil, Ian Covert, Su-In Lee
Estimating Shape Distances on Neural Representations with Limited Samples
Dean Pospisil, Brett Larsen, Sarah Harvey et al.
Eureka: Human-Level Reward Design via Coding Large Language Models
Yecheng Jason Ma, William Liang, Guanzhi Wang et al.
Evaluating Language Model Agency Through Negotiations
Tim R. Davidson, Veniamin Veselovsky, Michal Kosinski et al.
Evaluating Large Language Models at Evaluating Instruction Following
Zhiyuan Zeng, Jiatong Yu, Tianyu Gao et al.
Evaluating Representation Learning on the Protein Structure Universe
Arian Jamasb, Alex Morehead, Chaitanya Joshi et al.
Evaluating the Zero-shot Robustness of Instruction-tuned Language Models
Jiuding Sun, Chantal Shaib, Byron Wallace
EventRPG: Event Data Augmentation with Relevance Propagation Guidance
Mingyuan Sun, Donghao Zhang, Zongyuan Ge et al.
Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing
Xinyu Hu, Pengfei Tang, Simiao Zuo et al.
ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis
Kensen Shi, Joey Hong, Yinlin Deng et al.
EX-Graph: A Pioneering Dataset Bridging Ethereum and X
Qian Wang, Zhen Zhang, Zemin Liu et al.
Expected flow networks in stochastic environments and two-player zero-sum games
Marco Jiralerspong, Bilun Sun, Danilo Vucetic et al.
Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection
Stefano Blumberg, Paddy Slator, Daniel Alexander
Explaining Kernel Clustering via Decision Trees
Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
Explaining Time Series via Contrastive and Locally Sparse Perturbations
Zichuan Liu, Yingying ZHANG, Tianchun Wang et al.
Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning
Mirco Mutti, Riccardo De Santi, Marcello Restelli et al.
Exploring Diffusion Time-steps for Unsupervised Representation Learning
Zhongqi Yue, Zhongqi Yue, Jiankun Wang et al.
Exploring Effective Stimulus Encoding via Vision System Modeling for Visual Prostheses
Chuanqing Wang, Di Wu, Chaoming Fang et al.
Exploring Target Representations for Masked Autoencoders
xingbin liu, Jinghao Zhou, Tao Kong et al.
Exploring the cloud of feature interaction scores in a Rashomon set
Sichao Li, Rong Wang, Quanling Deng et al.
Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow
Hanyu Zhou, Yi Chang, Haoyue Liu et al.
Exploring the Promise and Limits of Real-Time Recurrent Learning
Kazuki Irie, Anand Gopalakrishnan, Jürgen Schmidhuber
Exploring Weight Balancing on Long-Tailed Recognition Problem
Naoya Hasegawa, Issei Sato
Exposing Text-Image Inconsistency Using Diffusion Models
Mingzhen Huang, Shan Jia, Zhou Zhou et al.
Expressive Losses for Verified Robustness via Convex Combinations
Alessandro De Palma, Rudy R Bunel, Krishnamurthy Dvijotham et al.
Expressivity of ReLU-Networks under Convex Relaxations
Maximilian Baader, Mark N Müller, Yuhao Mao et al.
Extending Power of Nature from Binary to Real-Valued Graph Learning in Real World
Chunshu Wu, Ruibing Song, Chuan Liu et al.
Facing the Elephant in the Room: Visual Prompt Tuning or Full finetuning?
Cheng Han, Qifan Wang, Yiming Cui et al.
Fair and Efficient Contribution Valuation for Vertical Federated Learning
Zhenan Fan, Huang Fang, Xinglu Wang et al.
Fair Classifiers that Abstain without Harm
Tongxin Yin, Jean-Francois Ton, Ruocheng Guo et al.
FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs
Sepehr Dehdashtian, Lan Wang, Vishnu Boddeti
fairret: a Framework for Differentiable Fairness Regularization Terms
Maarten Buyl, MaryBeth Defrance, Tijl De Bie
FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling
Yu Tian, Min Shi, Yan Luo et al.
FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis
Raman Dutt, Ondrej Bohdal, Sotirios Tsaftaris et al.
Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models
Andrew Engel, Zhichao Wang, Natalie Frank et al.
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
Yair Gat, Nitay Calderon, Amir Feder et al.
Faithful Rule Extraction for Differentiable Rule Learning Models
Xiaxia Wang, David Jaime Tena Cucala, Bernardo Grau et al.
Faithful Vision-Language Interpretation via Concept Bottleneck Models
Songning Lai, Lijie Hu, Junxiao Wang et al.
Fake It Till Make It: Federated Learning with Consensus-Oriented Generation
Rui Ye, Yaxin Du, Zhenyang Ni et al.
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model
Karsten Roth, Lukas Thede, A. Sophia Koepke et al.
Fantastic Generalization Measures are Nowhere to be Found
Michael Gastpar, Ido Nachum, Jonathan Shafer et al.
Fast and unified path gradient estimators for normalizing flows
Lorenz Vaitl, Ludwig Winkler, Lorenz Richter et al.
Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature
Guangsheng Bao, Yanbin Zhao, Zhiyang Teng et al.
Fast-ELECTRA for Efficient Pre-training
Chengyu Dong, Liyuan Liu, Hao Cheng et al.
Fast Ensembling with Diffusion Schrödinger Bridge
Hyunsu Kim, Jongmin Yoon, Juho Lee
Fast Equilibrium of SGD in Generic Situations
Zhiyuan Li, Yi Wang, Zhiren Wang
Faster Approximation of Probabilistic and Distributional Values via Least Squares
Weida Li, Yaoliang Yu
Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers
Oren Mangoubi, Nisheeth Vishnoi