语言大模型 / LLM

Does Few-Shot Learning Help LLM Performance in Code Synthesis?

Derek Xu, Tong Xie, Botao Xia, Haoyu Li, Yunsheng Bai, Yizhou Sun, Wei Wang

专题命中 预训练与数据 ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Language Models and Cycle Consistency for Self-Reflective Machine Translation

Jianqiao Wangni

专题命中 预训练与数据 ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Watermarking Makes Language Models Radioactive

Tom Sander, Pierre Fernandez, Alain Durmus, Matthijs Douze, Teddy Furon

专题命中 预训练与数据 ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Published at NeurIPS 2024 (Spotlight). Code at https://github.com/facebookresearch/radioactive-watermark - webpage at https://pierrefdz.github.io/publications/radioactive/

Multi-LLM QA with Embodied Exploration

Bhrij Patel, Vishnu Sashank Dorbala, Amrit Singh Bedi, Dinesh Manocha

专题命中 预训练与数据 ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 16 pages, 9 Figures, 5 Tables

PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs

Charlie Hou, Akshat Shrivastava, Hongyuan Zhan, Rylan Conway, Trang Le, Adithya Sagar, Giulia Fanti, Daniel Lazar

专题命中 预训练与数据 ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments ICML 2024 (Oral). Latest revision corrects a discussion on concurrent work arXiv:2403.01749. We described their work as reliant on using closed-sourced models when in reality they also evaluate and use open source models. This has been corrected in this version

Understanding and Modeling Job Marketplace with Pretrained Language Models

Yaochen Zhu, Liang Wu, Binchi Zhang, Song Wang, Qi Guo, Liangjie Hong, Luke Simon, Jundong Li

专题命中 预训练与数据 ：language model(title,abstract)；foundation model(abstract)；pretraining(abstract)；prompting(abstract)

Comments accepted by CIKM'24 applied research track

Automatic Generation of Behavioral Test Cases For Natural Language Processing Using Clustering and Prompting

Ying Li, Rahul Singh, Tarun Joshi, Agus Sudjianto

专题命中 预训练与数据 ：prompting(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

AesExpert: Towards Multi-modality Foundation Model for Image Aesthetics Perception

Yipo Huang, Xiangfei Sheng, Zhichao Yang, Quan Yuan, Zhichao Duan, Pengfei Chen, Leida Li, Weisi Lin, Guangming Shi

专题命中 预训练与数据 ：foundation model(title,abstract)；large language model(abstract)；language model(abstract)；instruction tuning(abstract)

Comments Accepted by ACMMM24

LMDX: Language Model-based Document Information Extraction and Localization

Vincent Perot, Kai Kang, Florian Luisier, Guolong Su, Xiaoyu Sun, Ramya Sree Boppana, Zilong Wang, Zifeng Wang, Jiaqi Mu, Hao Zhang, Chen-Yu Lee, Nan Hua

专题命中 预训练与数据 ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI、cs.LG

PRESTO: Progressive Pretraining Enhances Synthetic Chemistry Outcomes

He Cao, Yanjun Shao, Zhiyuan Liu, Zijing Liu, Xiangru Tang, Yuan Yao, Yu Li

专题命中 预训练与数据 ：pretraining(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

LLM Attributor: Interactive Visual Attribution for LLM Generation

Seongmin Lee, Zijie J. Wang, Aishwarya Chakravarthy, Alec Helbling, ShengYun Peng, Mansi Phute, Duen Horng Chau, Minsuk Kahng

专题命中 预训练与数据 ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 8 pages, 3 figures, For a video demo, see https://youtu.be/mIG2MDQKQxM

Rephrase, Augment, Reason: Visual Grounding of Questions for Vision-Language Models

Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal

专题命中 预训练与数据 ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments ICLR 2024 camera-ready (23 pages), Code: https://github.com/archiki/RepARe

ReAct Meets ActRe: When Language Agents Enjoy Training Data Autonomy

Zonghan Yang, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Yang Liu

专题命中 预训练与数据 ：language agent(title,abstract)；foundation model(abstract)；prompting(abstract)；分类 cs.CL、cs.AI、cs.LG

VBART: The Turkish LLM

Meliksah Turker, Mehmet Erdi Ari, Aydin Han

专题命中 预训练与数据 ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Reframe Anything: LLM Agent for Open World Video Reframing

Jiawang Cao, Yongliang Wu, Weiheng Chi, Wenbo Zhu, Ziyue Su, Jay Wu

专题命中 预训练与数据 ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；foundation model(abstract)

Comments 14 pages, 6 figures

ChatMusician: Understanding and Generating Music Intrinsically with LLM

Ruibin Yuan, Hanfeng Lin, Yi Wang, Zeyue Tian, Shangda Wu, Tianhao Shen, Ge Zhang, Yuhang Wu, Cong Liu, Ziya Zhou, Ziyang Ma, Liumeng Xue, Ziyu Wang, Qin Liu, Tianyu Zheng, Yizhi Li, Yinghao Ma, Yiming Liang, Xiaowei Chi, Ruibo Liu, Zili Wang, Pengfei Li, Jingcheng Wu, Chenghua Lin, Qifeng Liu, Tao Jiang, Wenhao Huang, Wenhu Chen, Emmanouil Benetos, Jie Fu, Gus Xia, Roger Dannenberg, Wei Xue, Shiyin Kang, Yike Guo

专题命中 预训练与数据 ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments GitHub: https://shanghaicannon.github.io/ChatMusician/

NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated Data

Sergei Bogdanov, Alexandre Constantin, Timothée Bernard, Benoit Crabbé, Etienne Bernard

专题命中 预训练与数据 ：LLM(title)；large language model(abstract)；language model(abstract)；foundation model(abstract)

Unifying Image Processing as Visual Prompting Question Answering

Yihao Liu, Xiangyu Chen, Xianzheng Ma, Xintao Wang, Jiantao Zhou, Yu Qiao, Chao Dong

专题命中 预训练与数据 ：prompting(title,abstract)；large language model(abstract)；language model(abstract)；pretraining(abstract)

Comments 16 pages, 12 figures

Personas as a Way to Model Truthfulness in Language Models

Nitish Joshi, Javier Rando, Abulhair Saparov, Najoung Kim, He He

专题命中 预训练与数据 ：language model(title,abstract)；large language model(abstract)；pretraining(abstract)；分类 cs.CL、cs.AI、cs.LG

Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study

Boxin Wang, Wei Ping, Peng Xu, Lawrence McAfee, Zihan Liu, Mohammad Shoeybi, Yi Dong, Oleksii Kuchaiev, Bo Li, Chaowei Xiao, Anima Anandkumar, Bryan Catanzaro

专题命中 预训练与数据 ：language model(title,abstract)；foundation model(abstract)；pretraining(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments EMNLP 2023

Efficiently Adapting Pretrained Language Models To New Languages

Zoltan Csaki, Pian Pawakapan, Urmish Thakker, Qiantong Xu

专题命中 预训练与数据 ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted to "The third Neurips Workshop on Efficient Natural Language and Speech Processing 2023" (ENLSP-III)

AuthentiGPT: Detecting Machine-Generated Text via Black-Box Language Models Denoising

Zhen Guo, Shangdi Yu

专题命中 预训练与数据 ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Make LLM a Testing Expert: Bringing Human-like Interaction to Mobile GUI Testing via Functionality-aware Decisions

Zhe Liu, Chunyang Chen, Junjie Wang, Mengzhuo Chen, Boyu Wu, Xing Che, Dandan Wang, Qing Wang

专题命中 预训练与数据 ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；prompting(abstract)

Comments Accepted by IEEE/ACM International Conference on Software Engineering 2024 (ICSE 2024). arXiv admin note: substantial text overlap with arXiv:2305.09434

To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis

Fuzhao Xue, Yao Fu, Wangchunshu Zhou, Zangwei Zheng, Yang You

专题命中 预训练与数据 ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted at NeurIPS 2023

Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes

Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alexander Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister

专题命中 预训练与数据 ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted to Findings of ACL 2023

BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting

Zheng-Xin Yong, Hailey Schoelkopf, Niklas Muennighoff, Alham Fikri Aji, David Ifeoluwa Adelani, Khalid Almubarak, M Saiful Bari, Lintang Sutawika, Jungo Kasai, Ahmed Baruwa, Genta Indra Winata, Stella Biderman, Edward Raff, Dragomir Radev, Vassilina Nikoulina

专题命中 预训练与数据 ：prompting(title,abstract)；language model(abstract)；pretraining(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments ACL 2023

Don't Prompt, Search! Mining-based Zero-Shot Learning with Language Models

Mozes van de Kar, Mengzhou Xia, Danqi Chen, Mikel Artetxe

专题命中 预训练与数据 ：language model(title,abstract)；pretraining(abstract)；prompting(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments EMNLP 2022

Deep Bidirectional Language-Knowledge Graph Pretraining

Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D Manning, Percy Liang, Jure Leskovec

专题命中 预训练与数据 ：pretraining(title,abstract)；language model(abstract)；foundation model(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Published at NeurIPS 2022. Code, data, and trained models are available at https://github.com/michiyasunaga/dragon

Continual Training of Language Models for Few-Shot Learning

Zixuan Ke, Haowei Lin, Yijia Shao, Hu Xu, Lei Shu, Bing Liu

专题命中 预训练与数据 ：language model(title,abstract)；large language model(abstract)；post-training(abstract)；分类 cs.CL、cs.AI、cs.LG

Journal ref EMNLP 2022

The Geometry of Dialogue: Graphing Language Models to Reveal Synergistic Teams for Multi-Agent Collaboration

对话的几何学：基于图谱的语言模型揭示多智能体协作的协同团队

Kotaro Furuya, Yuichi Kitagawa

专题命中 预训练与数据 ：language model(title,abstract)；LLM(abstract,comments)；large language model(abstract)；分类 cs.CL、cs.AI

AI总结 本文提出一种基于交互的自动团队组建框架，通过构建语言模型图谱揭示多智能体协作的协同团队，实验表明其能发现功能一致的团队并优于随机基线。

Comments Accepted at the AAAI-26 Workshop on LLM-based Multi-Agent Systems: Towards Responsible, Reliable, and Scalable Agentic Systems (LaMAS 2026) as an oral presentation