ICLR Poster Papers
5,330 papers found • Page 7 of 107
Balanced Ranking with Relative Centrality: A multi-core periphery perspective
Chandra Sekhar Mukherjee, Jiapeng Zhang
Balancing Act: Diversity and Consistency in Large Language Model Ensembles
Ahmed Abdulaal, Chen Jin, Nina Montaña-Brown et al.
Balancing Bias in Two-sided Markets for Fair Stable Matchings
Siyuan Wu, Leong Hou U, Panagiotis Karras
BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games
Davide Paglieri, Bartłomiej Cupiał, Samuel Coward et al.
BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping
Aly Lidayan, Michael Dennis, Stuart Russell
Bandit Learning in Matching Markets with Indifference
Fang Kong, Jingqi Tang, Mingzhu Li et al.
BANGS: Game-theoretic Node Selection for Graph Self-Training
Fangxin Wang, Kay Liu, Sourav Medya et al.
Basis Sharing: Cross-Layer Parameter Sharing for Large Language Model Compression
Jingcun Wang, Yu-Guang Chen, Ing-Chao Lin et al.
Bayesian Analysis of Combinatorial Gaussian Process Bandits
Jack Sandberg, Niklas Åkerblom, Morteza Haghir Chehreghani
Bayesian Experimental Design Via Contrastive Diffusions
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez et al.
Bayesian Image Regression with Soft-thresholded Conditional Autoregressive Prior
Yuliang Xu, Jian Kang
Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
Alan Amin, Nate Gruver, Yilun Kuang et al.
Bayesian Optimization via Continual Variational Last Layer Training
Paul Brunzema, Mikkel Jordahn, John Willes et al.
Bayesian Regularization of Latent Representation
Chukwudi Paul Obite, Zhi Chang, Keyan Wu et al.
Bayesian Treatment of the Spectrum of the Empirical Kernel in (Sub)Linear-Width Neural Networks
Ouns El Harzli, Bernardo Grau
Bayesian WeakS-to-Strong from Text Classification to Generation
Ziyun Cui, Ziyang Zhang, Guangzhi Sun et al.
BBCaL: Black-box Backdoor Detection under the Causality Lens
Zihan Guan, Junfeng Guo, Mengxuan Hu et al.
BEEM: Boosting Performance of Early Exit DNNs using Multi-Exit Classifiers as Experts
Divya Jyoti Bajpai, Manjesh Kumar Hanawal
Be More Diverse than the Most Diverse: Optimal Mixtures of Generative Models via Mixture-UCB Bandit Algorithms
Parham Rezaei, Farzan Farnia, Cheuk Ting Li
Benchmarking Agentic Workflow Generation
Shuofei Qiao, Runnan Fang, Zhisong Qiu et al.
Benchmarking LLMs' Judgments with No Gold Standard
Shengwei Xu, Yuxuan Lu, Grant Schoenebeck et al.
Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent
Yangning Li, Yinghui Li, Xinyu Wang et al.
Benchmarking Predictive Coding Networks -- Made Simple
Luca Pinchetti, Chang Qi, Oleh Lokshyn et al.
Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset
Yingzi Ma, Jiongxiao Wang, Fei Wang et al.
Benign Overfitting in Out-of-Distribution Generalization of Linear Models
Shange Tang, Jiayun Wu, Jianqing Fan et al.
BenTo: Benchmark Reduction with In-Context Transferability
Hongyu Zhao, Ming Li, Lichao Sun et al.
Better autoregressive regression with LLMs via regression-aware fine-tuning
Michal Lukasik, Zhao Meng, Harikrishna Narasimhan et al.
Better Instruction-Following Through Minimum Bayes Risk
Ian Wu, Patrick Fernandes, Amanda Bertsch et al.
Better than Your Teacher: LLM Agents that learn from Privileged AI Feedback
Sanjiban Choudhury, Paloma Sodhi
Beware of Calibration Data for Pruning Large Language Models
Yixin Ji, Yang Xiang, Juntao Li et al.
Beyond Autoregression: Discrete Diffusion for Complex Reasoning and Planning
Jiacheng Ye, Jiahui Gao, Shansan Gong et al.
Beyond Autoregression: Fast LLMs via Self-Distillation Through Time
Justin Deschenaux, Caglar Gulcehre
Beyond Canonicalization: How Tensorial Messages Improve Equivariant Message Passing
Peter Lippmann, Gerrit Gerhartz, Roman Remme et al.
Beyond Circuit Connections: A Non-Message Passing Graph Transformer Approach for Quantum Error Mitigation
Tianyi Bao, Xinyu Ye, Hang Ruan et al.
Beyond Content Relevance: Evaluating Instruction Following in Retrieval Models
Jianqun Zhou, Yuanlei Zheng, Wei Chen et al.
Beyond correlation: The impact of human uncertainty in measuring the effectiveness of automatic evaluation and LLM-as-a-judge
Aparna Elangovan, Lei Xu, Jongwoo Ko et al.
Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration
Heyang Zhao, Xingrui Yu, David Bossens et al.
Beyond Graphs: Can Large Language Models Comprehend Hypergraphs?
Yifan Feng, Chengwu Yang, Xingliang Hou et al.
Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
Qi Zhang, Yifei Wang, Jingyi Cui et al.
Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix
Yingyu Liang, Jiangxuan Long, Zhenmei Shi et al.
Beyond Mere Token Analysis: A Hypergraph Metric Space Framework for Defending Against Socially Engineered LLM Attacks
Manohar Kaul, Aditya Saibewar, Sadbhavana Babar
Beyond Model Collapse: Scaling Up with Synthesized Data Requires Verification
Yunzhen Feng, Elvis Dohmatob, Pu Yang et al.
Beyond Next Token Prediction: Patch-Level Training for Large Language Models
Chenze Shao, Fandong Meng, Jie Zhou
Beyond Random Augmentations: Pretraining with Hard Views
Fabio Ferreira, Ivo Rapant, Jörg Franke et al.
Beyond Random Masking: When Dropout meets Graph Convolutional Networks
Yuankai Luo, Xiao-Ming Wu, Hao Zhu
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction
Junjie Xu, Artem Moskalev, Tommaso Mansi et al.
Beyond Single Concept Vector: Modeling Concept Subspace in LLMs with Gaussian Distribution
Haiyan Zhao, Heng Zhao, Bo Shen et al.
Beyond single neurons: population response geometry in digital twins of mouse visual cortex
Dario Liscai, Emanuele Luconi, Alessandro Marin Vargas et al.
Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks
Rui Hu, Yifan Zhang, Zhuoran Li et al.
Beyond Surface Structure: A Causal Assessment of LLMs' Comprehension ability
Yujin Han, Lei Xu, Sirui Chen et al.