"large language models" Papers

Evolving Subnetwork Training for Large Language Models

hanqi li, Lu Chen, Da Ma et al.

ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking

Wenshuo Li, Xinghao Chen, Han Shu et al.

Exploiting Code Symmetries for Learning Program Semantics

Kexin Pei, Weichen Li, Qirui Jin et al.

Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations

Likang Wu, Zhaopeng Qiu, Zhi Zheng et al.

Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation

Zhewei Yao, Xiaoxia Wu, Cheng Li et al.

Extreme Compression of Large Language Models via Additive Quantization

Vage Egiazarian, Andrei Panferov, Denis Kuznedelev et al.

FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models

Jingwei Sun, Ziyue Xu, Hongxu Yin et al.

Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes

Zhen Qin, Daoyuan Chen, Bingchen Qian et al.

FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering

Zhenyu Li, Sunqi Fan, Yu Gu et al.

Flextron: Many-in-One Flexible Large Language Model

Ruisi Cai, Saurav Muralidharan, Greg Heinrich et al.

Fluctuation-Based Adaptive Structured Pruning for Large Language Models

Yongqi An, Xu Zhao, Tao Yu et al.

From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning

Wei Chen, Zhen Huang, Liang Xie et al.

Fundamental Limitations of Alignment in Large Language Models

Yotam Wolf, Noam Wies, Oshri Avnery et al.

GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting

Xiaoyu Zhou, Xingjian Ran, Yajiao Xiong et al.

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Jiawei Zhao, Zhenyu Zhang, Beidi Chen et al.

Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought

Zhen-Yu Zhang, Siwei Han, Huaxiu Yao et al.

Get an A in Math: Progressive Rectification Prompting

Zhenyu Wu, Meng Jiang, Chao Shen

GiLOT: Interpreting Generative Language Models via Optimal Transport

Xuhong Li, Jiamin Chen, Yekun Chai et al.

GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks

Shivanshu Gupta, Clemens Rosenbaum, Ethan R. Elenberg

GliDe with a CaPE: A Low-Hassle Method to Accelerate Speculative Decoding

Cunxiao Du, Jing Jiang, Xu Yuanchen et al.

Graph Neural Prompting with Large Language Models

Yijun Tian, Huan Song, Zichen Wang et al.

Graph of Thoughts: Solving Elaborate Problems with Large Language Models

Maciej Besta, Nils Blach, Ales Kubicek et al.

GRATH: Gradual Self-Truthifying for Large Language Models

Weixin Chen, Dawn Song, Bo Li

Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation

Luca Beurer-Kellner, Marc Fischer, Martin Vechev

HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal

Mantas Mazeika, Long Phan, Xuwang Yin et al.

Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions

Jingtan Wang, Xiaoqiang Lin, Rui Qiao et al.

History Matters: Temporal Knowledge Editing in Large Language Model

Xunjian Yin, Jin Jiang, Liming Yang et al.

Hot or Cold? Adaptive Temperature Sampling for Code Generation with Large Language Models

Yuqi Zhu, Jia Li, Ge Li et al.

How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?

Ryan Liu, Theodore R Sumers, Ishita Dasgupta et al.

How to Protect Copyright Data in Optimization of Large Language Models?

Timothy Chu, Zhao Song, Chiwun Yang

Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks

Akshay Kumar Jagadish, Julian Coda-Forno, Mirko Thalmann et al.

Image Captioning with Multi-Context Synthetic Data

Implicit meta-learning may lead language models to trust more reliable sources

Dmitrii Krasheninnikov, Egor Krasheninnikov, Bruno Mlodozeniec et al.

In-Context Learning Agents Are Asymmetric Belief Updaters

Johannes A. Schubert, Akshay Kumar Jagadish, Marcel Binz et al.

In-Context Principle Learning from Mistakes

Tianjun Zhang, Aman Madaan, Luyu Gao et al.

In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation

Shiqi Chen, Miao Xiong, Junteng Liu et al.

In-Context Unlearning: Language Models as Few-Shot Unlearners

Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju

In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering

Sheng Liu, Haotian Ye, Lei Xing et al.

InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining

Boxin Wang, Wei Ping, Lawrence McAfee et al.

InstructSpeech: Following Speech Editing Instructions via Large Language Models

Rongjie Huang, Ruofan Hu, Yongqi Wang et al.

Integrated Hardware Architecture and Device Placement Search

Irene Wang, Jakub Tarnawski, Amar Phanishayee et al.

Interpreting and Improving Large Language Models in Arithmetic Calculation

Wei Zhang, Wan Chaoqun, Yonggang Zhang et al.

Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective

Fabian Falck, Ziyu Wang, Christopher Holmes

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights $\textit{Irreversibly}$ and $\textit{Monotonically}$ Impairs ``Difficult" Downstream Tasks in LLMs

Lu Yin, Ajay Jaiswal, Shiwei Liu et al.

KAM-CoT: Knowledge Augmented Multimodal Chain-of-Thoughts Reasoning

Debjyoti Mondal, Suraj Modi, Subhadarshi Panda et al.

Knowledge Graph Prompting for Multi-Document Question Answering

Yu Wang, Nedim Lipka, Ryan A. Rossi et al.

Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game

Zelai Xu, Chao Yu, Fei Fang et al.

Language Generation with Strictly Proper Scoring Rules

Chenze Shao, Fandong Meng, Yijin Liu et al.

Language Models Represent Beliefs of Self and Others

Wentao Zhu, Zhining Zhang, Yizhou Wang

Large Language Models Are Clinical Reasoners: Reasoning-Aware Diagnosis Framework with Prompt-Generated Rationales

Taeyoon Kwon, Kai Ong, Dongjin Kang et al.