ICML "large language models" Papers

180 papers found • Page 3 of 4

LLM-Empowered State Representation for Reinforcement Learning

Boyuan Wang, Yun Qu, Yuhang Jiang et al.

ICML 2024posterarXiv:2407.13237

LoCoCo: Dropping In Convolutions for Long Context Compression

Ruisi Cai, Yuandong Tian, Zhangyang “Atlas” Wang et al.

ICML 2024posterarXiv:2406.05317

LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Yiran Ding, Li Lyna Zhang, Chengruidong Zhang et al.

ICML 2024posterarXiv:2402.13753

LoRA+: Efficient Low Rank Adaptation of Large Models

Soufiane Hayou, Nikhil Ghosh, Bin Yu

ICML 2024posterarXiv:2402.12354

LoRAP: Transformer Sub-Layers Deserve Differentiated Structured Compression for Large Language Models

guangyan li, Yongqiang Tang, Wensheng Zhang

ICML 2024posterarXiv:2404.09695

LoRA Training in the NTK Regime has No Spurious Local Minima

Uijeong Jang, Jason Lee, Ernest Ryu

ICML 2024posterarXiv:2402.11867

LQER: Low-Rank Quantization Error Reconstruction for LLMs

Cheng Zhang, Jianyi Cheng, George Constantinides et al.

ICML 2024posterarXiv:2402.02446

Magicoder: Empowering Code Generation with OSS-Instruct

Yuxiang Wei, Zhe Wang, Jiawei Liu et al.

ICML 2024posterarXiv:2312.02120

MathScale: Scaling Instruction Tuning for Mathematical Reasoning

Zhengyang Tang, Xingxing Zhang, Benyou Wang et al.

ICML 2024posterarXiv:2403.02884

Model Alignment as Prospect Theoretic Optimization

Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff et al.

ICML 2024spotlightarXiv:2402.01306

Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews

Weixin Liang, Zachary Izzo, Yaohui Zhang et al.

ICML 2024posterarXiv:2403.07183

Multicalibration for Confidence Scoring in LLMs

Gianluca Detommaso, Martin A Bertran, Riccardo Fogliato et al.

ICML 2024posterarXiv:2404.04689

Neighboring Perturbations of Knowledge Editing on Large Language Models

Jun-Yu Ma, Zhen-Hua Ling, Ningyu Zhang et al.

ICML 2024posterarXiv:2401.17623

NExT: Teaching Large Language Models to Reason about Code Execution

Ansong Ni, Miltiadis Allamanis, Arman Cohan et al.

ICML 2024posterarXiv:2404.14662

Non-Vacuous Generalization Bounds for Large Language Models

Sanae Lotfi, Marc Finzi, Yilun Kuang et al.

ICML 2024posterarXiv:2312.17173

Online Speculative Decoding

Xiaoxuan Liu, Lanxiang Hu, Peter Bailis et al.

ICML 2024posterarXiv:2310.07177

On Prompt-Driven Safeguarding for Large Language Models

Chujie Zheng, Fan Yin, Hao Zhou et al.

ICML 2024posterarXiv:2401.18018

OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models

Fuzhao Xue, Zian Zheng, Yao Fu et al.

ICML 2024posterarXiv:2402.01739

Optimizing Watermarks for Large Language Models

Bram Wouters

ICML 2024posterarXiv:2312.17295

OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models

Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell

ICML 2024posterarXiv:2402.10172

Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity

Lu Yin, You Wu, Zhenyu Zhang et al.

ICML 2024posterarXiv:2310.05175

PARDEN, Can You Repeat That? Defending against Jailbreaks via Repetition

Ziyang Zhang, Qizhen Zhang, Jakob Foerster

ICML 2024posterarXiv:2405.07932

PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning

Hyeong Kyu Choi, Sharon Li

ICML 2024oralarXiv:2405.02501

Position: A Call for Embodied AI

Giuseppe Paolo, Jonas Gonzalez-Billandon, Balázs Kégl

ICML 2024poster

Position: A Roadmap to Pluralistic Alignment

Taylor Sorensen, Jared Moore, Jillian Fisher et al.

ICML 2024poster

Position: Building Guardrails for Large Language Models Requires Systematic Design

Yi DONG, Ronghui Mu, Gaojie Jin et al.

ICML 2024poster

Position: Foundation Agents as the Paradigm Shift for Decision Making

Xiaoqian Liu, Xingzhou Lou, Jianbin Jiao et al.

ICML 2024posterarXiv:2405.17009

Position: Key Claims in LLM Research Have a Long Tail of Footnotes

Anna Rogers, Sasha Luccioni

ICML 2024posterarXiv:2308.07120

Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI

Francisco Eiras, Aleksandar Petrov, Bertie Vidgen et al.

ICML 2024poster

Position: On the Possibilities of AI-Generated Text Detection

Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu et al.

ICML 2024poster

Position: Stop Making Unscientific AGI Performance Claims

Patrick Altmeyer, Andrew Demetriou, Antony Bartlett et al.

ICML 2024posterarXiv:2402.03962

Position: What Can Large Language Models Tell Us about Time Series Analysis

Ming Jin, Yi-Fan Zhang, Wei Chen et al.

ICML 2024posterarXiv:2402.02713

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data

Fahim Tajwar, Anikait Singh, Archit Sharma et al.

ICML 2024posterarXiv:2404.14367

Premise Order Matters in Reasoning with Large Language Models

Xinyun Chen, Ryan Chi, Xuezhi Wang et al.

ICML 2024posterarXiv:2402.08939

Privacy-Preserving Instructions for Aligning Large Language Models

Da Yu, Peter Kairouz, Sewoong Oh et al.

ICML 2024posterarXiv:2402.13659

Promptbreeder: Self-Referential Self-Improvement via Prompt Evolution

Chrisantha Fernando, Dylan Banarse, Henryk Michalewski et al.

ICML 2024posterarXiv:2309.16797

Prompt Sketching for Large Language Models

Luca Beurer-Kellner, Mark Müller, Marc Fischer et al.

ICML 2024posterarXiv:2311.04954

Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models

Peijie Dong, Lujun Li, Zhenheng Tang et al.

ICML 2024posterarXiv:2406.02924

Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning

Jing Xu, Jingzhao Zhang

ICML 2024posterarXiv:2405.02596

Repeat After Me: Transformers are Better than State Space Models at Copying

Samy Jelassi, David Brandfonbrener, Sham Kakade et al.

ICML 2024posterarXiv:2402.01032

Rethinking Generative Large Language Model Evaluation for Semantic Comprehension

Fangyun Wei, Xi Chen, Lin Luo

ICML 2024posterarXiv:2403.07872

Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Yihua Zhang, Pingzhi Li, Junyuan Hong et al.

ICML 2024posterarXiv:2402.11592

Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models

Fangzhao Zhang, Mert Pilanci

ICML 2024posterarXiv:2402.02347

RLVF: Learning from Verbal Feedback without Overgeneralization

Moritz Stephan, Alexander Khazatsky, Eric Mitchell et al.

ICML 2024posterarXiv:2402.10893

RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation

Mahdi Nikdan, Soroush Tabesh, Elvir Crnčević et al.

ICML 2024posterarXiv:2401.04679

Scaling Laws for Fine-Grained Mixture of Experts

Jan Ludziejewski, Jakub Krajewski, Kamil Adamczewski et al.

ICML 2024posterarXiv:2402.07871

SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models

Xiaoxuan Wang, ziniu hu, Pan Lu et al.

ICML 2024posterarXiv:2307.10635

Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulation

Xianghe Pang, shuo tang, Rui Ye et al.

ICML 2024spotlightarXiv:2402.05699

SelfIE: Self-Interpretation of Large Language Model Embeddings

Haozhe Chen, Carl Vondrick, Chengzhi Mao

ICML 2024posterarXiv:2403.10949

Should we be going MAD? A Look at Multi-Agent Debate Strategies for LLMs

Andries Smit, Nathan Grinsztajn, Paul Duckworth et al.

ICML 2024posterarXiv:2311.17371