ICLR Papers
6,124 papers found • Page 8 of 123
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 FVD: An Enhanced Evaluation Metrics for Video Generation Distribution Quality
Ge Ya Luo, Gian M Favero, Zhi Hao Luo 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.
Beyond the convexity assumption: Realistic tabular data generation under quantifier-free real linear constraints
Mihaela Stoian, Eleonora Giunchiglia
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Clemencia Siro, Guy Gur-Ari, Gaurav Mishra et al.
Beyond Worst-Case Dimensionality Reduction for Sparse Vectors
Sandeep Silwal, David Woodruff, Qiuyi (Richard) Zhang
Bias Mitigation in Graph Diffusion Models
Meng Yu, Kun Zhan
Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling
Yuejiang Liu, Jubayer Hamid, Annie Xie et al.
Bi-Factorial Preference Optimization: Balancing Safety-Helpfulness in Language Models
Wenxuan Zhang, Philip Torr, Mohamed Elhoseiny et al.
BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions
Terry Yue Zhuo, Minh Chien Vu, Jenny Chim et al.
BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks
Juan A. Rodriguez, Xiangru Jian, Siba Smarak Panigrahi et al.
BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities
Shaozhe Hao, Xuantong LIU, Xianbiao Qi et al.
Bilinear MLPs enable weight-based mechanistic interpretability
Michael Pearce, Thomas Dooms, Alice Rigg et al.
BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models
Xingyu Zheng, Xianglong Liu, Haotong Qin et al.
Binary Losses for Density Ratio Estimation
Werner Zellinger
BingoGuard: LLM Content Moderation Tools with Risk Levels
Fan Yin, Philippe Laban, XIANGYU PENG et al.
BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments
Yusuf Roohani, Andrew Lee, Qian Huang et al.
Biologically Constrained Barrel Cortex Model Integrates Whisker Inputs and Replicates Key Brain Network Dynamics
Tianfang Zhu, Dongli Hu, Jiandong Zhou et al.
Biologically Plausible Brain Graph Transformer
Ciyuan Peng, Yuelong Huang, Qichao Dong et al.
Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences
Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl et al.
BIRD: A Trustworthy Bayesian Inference Framework for Large Language Models
Yu Feng, Ben Zhou, Weidong Lin et al.
BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics
Lukas Rauch, Raphael Schwinger, Moritz Wirth et al.
Bisimulation Metric for Model Predictive Control
Yutaka Shimizu, Masayoshi Tomizuka
BitStack: Any-Size Compression of Large Language Models in Variable Memory Environments
Xinghao Wang, Pengyu Wang, Bo Wang et al.
Black-Box Detection of Language Model Watermarks
Thibaud Gloaguen, Nikola Jovanović, Robin Staab et al.
Black Sheep in the Herd: Playing with Spuriously Correlated Attributes for Vision-Language Recognition
Xinyu Tian, Shu Zou, Zhaoyuan Yang et al.
BLEND: Behavior-guided Neural Population Dynamics Modeling via Privileged Knowledge Distillation
Zhengrui Guo, Fangxu Zhou, Wei Wu et al.
BlendRL: A Framework for Merging Symbolic and Neural Policy Learning
Hikaru Shindo, Quentin Delfosse, Devendra Singh Dhami et al.