Papers
Research Community Perspectives on “Intelligence” and Large Language Models
Bertram Højer, Terne Sasha Thorn Jakobsen, Anna Rogers et al.
Resource-Friendly Dynamic Enhancement Chain for Multi-Hop Question Answering
Binquan Ji, Haibo Luo, Yifei Lu et al.
Response Wide Shut? Surprising Observations in Basic Vision Language Model Capabilities
Shivam Chandhok, Wan-Cyuan Fan, Vered Shwartz et al.
Re-TASK: Revisiting LLM Tasks from Capability, Skill, and Knowledge Perspectives
Zhihu Wang, Shiwan Zhao, Yu Wang et al.
Rethinking Diverse Human Preference Learning through Principal Component Analysis
Feng Luo, Rui Yang, Hao Sun et al.
Rethinking Evaluation Metrics for Grammatical Error Correction: Why Use a Different Evaluation Process than Human?
Takumi Goto, Yusuke Sakai, Taro Watanabe
Rethinking Full Finetuning from Pretraining Checkpoints in Active Learning for African Languages
Bonaventure F. P. Dossou, Ines Arous, Jackie CK Cheung
Rethinking KenLM: Good and Bad Model Ensembles for Efficient Text Quality Filtering in Large Web Corpora
Yungi Kim, Hyunsoo Ha, Sukyung Lee et al.
Rethinking Prompt-based Debiasing in Large Language Model
Xinyi Yang, Runzhe Zhan, Shu Yang et al.
Rethinking Repetition Problems of LLMs in Code Generation
Yihong Dong, Yuchen Liu, Xue Jiang et al.
Rethinking Reward Model Evaluation Through the Lens of Reward Overoptimization
Sunghwan Kim, Dongjin Kang, Taeyoon Kwon et al.
Rethinking Semantic Parsing for Large Language Models: Enhancing LLM Performance with Semantic Hints
Kaikai An, Shuzheng Si, Helan Hu et al.
Rethinking Stateful Tool Use in Multi-Turn Dialogues: Benchmarks and Challenges
Hongru Wang, Wenyu Huang, Yufei Wang et al.
Rethinking Table Instruction Tuning
Naihao Deng, Rada Mihalcea
Rethinking the Role of Prompting Strategies in LLM Test-Time Scaling: A Perspective of Probability Theory
Yexiang Liu, Zekun Li, Zhi Fang et al.
Rethinking the Roles of Large Language Models in Chinese Grammatical Error Correction
Yinghui Li, Shang Qin, Jingheng Ye et al.
Retrieval-Augmented Fine-Tuning With Preference Optimization For Visual Program Generation
Deokhyung Kang, Jeonghun Cho, Yejin Jeon et al.
Retrieval-Augmented Generation Meets Local Languages for Improved Drug Information Access and Comprehension.
Ahmad Ibrahim Ismail, Bashirudeen Opeyemi Ibrahim, Olubayo Adekanmbi et al.
Retrieval-Augmented Process Reward Model for Generalizable Mathematical Reasoning
Jiachen Zhu, Congmin Zheng, Jianghao Lin et al.
Retrieval Models Aren’t Tool-Savvy: Benchmarking Tool Retrieval for Large Language Models
Zhengliang Shi, Yuhan Wang, Lingyong Yan et al.
Retrieve to Explain: Evidence-driven Predictions for Explainable Drug Target Identification
Ravi Patel, Angus Brayne, Rogier Hintzen et al.
Retrieving Argument Graphs Using Vision Transformers
Kilian Bartz, Mirko Lenz, Ralph Bergmann