paper-conference

FineReason: Evaluating and Improving LLMs' Deliberate Reasoning through Reflective Puzzle Solving
Many challenging reasoning tasks require not just rapid, intuitive responses, but a more deliberate, multi-step approach. Recent …
Guizhen Chen, Weiwen Xu, Hao Zhang, Hou Pong Chan, Chaoqun Liu, Lidong Bing, Deli Zhao, Anh Tuan Luu, Yu Rong
Preprint PDF Cite Code 📌ACL'25
FineReason: Evaluating and Improving LLMs' Deliberate Reasoning through Reflective Puzzle Solving
Analyzing LLMs' Knowledge Boundary Cognition Across Languages Through the Lens of Internal Representations
While understanding the knowledge boundaries of LLMs is crucial to prevent hallucination, research on knowledge boundaries of LLMs has …
Chenghao Xiao, Hou Pong Chan, Hao Zhang, Mahani Aljunied, Lidong Bing, Noura Al Moubayed, Yu Rong
Preprint PDF Cite Code Dataset Poster Slides 📌ACL'25
Analyzing LLMs' Knowledge Boundary Cognition Across Languages Through the Lens of Internal Representations
CoIR: A Comprehensive Benchmark for Code Information Retrieval Models
Despite the substantial success of Information Retrieval (IR) in various NLP tasks, most IR systems predominantly handle queries and …
Xiangyang Li, Kuicai Dong, Yi Quan Lee, Wei Xia, Yichun Yin, Hao Zhang, Yong Liu, Yasheng Wang, Ruiming Tang
Preprint PDF Cite Code Dataset Project 📌ACL'25
CoIR: A Comprehensive Benchmark for Code Information Retrieval Models
Adaptive Tool Use in Large Language Models with Meta-Cognition Trigger
Large language models (LLMs) have shown remarkable emergent capabilities, transforming the execution of functional tasks by leveraging …
Wenjun Li, Dexun Li, Kuicai Dong, Cong Zhang, Hao Zhang, Weiwen Liu, Yasheng Wang, Ruiming Tang, Yong Liu
Preprint PDF Cite 📌ACL'25
Adaptive Tool Use in Large Language Models with Meta-Cognition Trigger
CtrlA: Adaptive Retrieval-Augmented Generation via Inherent Control
Retrieval-augmented generation (RAG) has emerged as a promising solution for mitigating hallucinations of large language models (LLMs) …
Huanshuo Liu, Hao Zhang, Zhijiang Guo, Kuicai Dong, Xiangyang Li, Yi Quan Lee, Cong Zhang, Yong Liu
Preprint PDF Cite Code 📌ACL'25
CtrlA: Adaptive Retrieval-Augmented Generation via Inherent Control
RAPID: Efficient Retrieval-Augmented Long Text Generation with Writing Planning and Information Discovery
Generating knowledge-intensive and comprehensive long texts, such as encyclopedia articles, remains significant challenges for Large …
Hongchao Gu, Dexun Li, Kuicai Dong, Hao Zhang, Hang Lv, Hao Wang, Defu Lian, Yong Liu, Enhong Chen
Preprint PDF Cite 📌ACL'25
RAPID: Efficient Retrieval-Augmented Long Text Generation with Writing Planning and Information Discovery
Frame-Voyager: Learning to Query Frames for Video Large Language Models
Video Large Language Models (Video-LLMs) have made remarkable progress in video understanding tasks. However, they are constrained by …
Sicheng Yu, Chengkai Jin, Huanyu Wang, Zhenghao Chen, Sheng Jin, Zhongrong Zuo, Xioalei Xu, Zhenbang Sun, Bingni Zhang, Jiawei Wu, Hao Zhang, Qianru Sun
Preprint PDF Cite 📌ICLR'25
Frame-Voyager: Learning to Query Frames for Video Large Language Models
Reverse Modeling in Large Language Models
Humans are accustomed to reading and writing in a forward manner, and this natural bias extends to text understanding in …
Sicheng Yu, Yuanchen Xu, Cunxiao Du, Yanying Zhou, Minghui Qiu, Qianru Sun, Hao Zhang, Jiawei Wu
Preprint PDF Cite DOI 📌NAACL'25
Reverse Modeling in Large Language Models
MR-Ben: A Meta-Reasoning Benchmark for Evaluating System-2 Thinking in LLMs
Large language models (LLMs) have shown increasing capability in problem-solving and decision-making, largely based on the step-by-step …
Zhongshen Zeng, Yinhong Liu, Yingjia Wan, Jingyao Li, Pengguang Chen, Jianbo Dai, Yuxuan Yao, Rongwu Xu, Zehan Qi, Wanru Zhao, Linling Shen, Jianqiao Lu, Haochen Tan, Yukang Chen, Hao Zhang, Zhan Shi, Bailin Wang, Zhijiang Guo, Jiaya Jia
Preprint PDF Cite Code Dataset Project Poster 📌NeurIPS'24
MR-Ben: A Meta-Reasoning Benchmark for Evaluating System-2 Thinking in LLMs
DVD: Dynamic Contrastive Decoding for Knowledge Amplification in Multi-Document Question Answering
Large language models (LLMs) are widely used in question-answering (QA) systems but often generate information with hallucinations. …
Jing Jin, Houfeng Wang, Hao Zhang, Xiaoguang Li, Zhijiang Guo
PDF Cite Code DOI 📌EMNLP'24
DVD: Dynamic Contrastive Decoding for Knowledge Amplification in Multi-Document Question Answering