"large language models" Papers

EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty

Yuhui Li, Fangyun Wei, Chao Zhang et al.

eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data

Peng, Xinyi Ling, Ziru Chen et al.

EcomGPT: Instruction-Tuning Large Language Models with Chain-of-Task Tasks for E-commerce

Li Yangning, Shirong Ma, Xiaobin Wang et al.

EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism

Yanxi Chen, Xuchen Pan, Yaliang Li et al.

Efficient Exploration for LLMs

Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao et al.

Emergent Visual-Semantic Hierarchies in Image-Text Representations

Morris Alper, Hadar Averbuch-Elor

Enhancing Job Recommendation through LLM-Based Generative Adversarial Networks

Yingpeng Du, Di Luo, Rui Yan et al.

Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection

Chentao Cao, Zhun Zhong, Zhanke Zhou et al.

Evaluating Quantized Large Language Models

Shiyao Li, Xuefei Ning, Luning Wang et al.

Evaluation of LLMs on Syntax-Aware Code Fill-in-the-Middle Tasks

Linyuan Gong, Sida Wang, Mostafa Elhoushi et al.

Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model

Fei Liu, Tong Xialiang, Mingxuan Yuan et al.

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.

FedVAD: Enhancing Federated Video Anomaly Detection with GPT-Driven Semantic Distillation

Fan Qi, Ruijie Pan, Huaiwen Zhang 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.