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Focuses on research that actively explores methods and strategies to ensure language models' outputs align with human values, ethics, and intentions, constituting a significant portion of the paper's content.
When Do Language Models Endorse Limitations on Human Rights Principles? Keenan Samway Nicole Miu Takagi Rada Mihalcea Bernhard Schölkopf Ilias Chalkidis Daniel Hershcovich Zhijing Jin | |||
 RubricBench: Aligning Model-Generated Rubrics with Human Standards Qiyuan Zhang Junyi Zhou Yufei Wang Fuyuan Lyu Yidong Ming ...Qingfeng Sun Kai Zheng Peng Kang Xue Liu Chen Ma | |||
 How Small Can 6G Reason? Scaling Tiny Language Models for AI-Native Networks Mohamed Amine Ferrag Abderrahmane Lakas Merouane Debbah | |||
 FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents Qizheng Li Yifei Zhang Xiao Yang Xu Yang Zhuo Wang Weiqing Liu Jiang Bian | |||
 When Numbers Tell Half the Story: Human-Metric Alignment in Topic Model Evaluation Thibault Prouteau Francis Lareau Nicolas Dugué Jean-Charles Lamirel Christophe Malaterre | |||
 DEP: A Decentralized Large Language Model Evaluation Protocol Jianxiang Peng Junhao Li Hongxiang Wang Haocheng Lyu Hui Guo ...Tianyu Dong Juesi Xiao Lei Yang Yuqi Ren Deyi Xiong | |||
 DARE-bench: Evaluating Modeling and Instruction Fidelity of LLMs in Data Science Fan Shu Yite Wang Ruofan Wu Boyi Liu Zhewei Yao Yuxiong He Feng Yan | |||
 CAMEL: Confidence-Gated Reflection for Reward Modeling Zirui Zhu Hailun Xu Yang Luo Yong Liu Kanchan Sarkar Kun Xu Yang You | |||
 QEDBENCH: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs Santiago Gonzalez Alireza Amiri Bavandpour Peter Ye Edward Zhang Ruslans Aleksejevs ...Sibel Yalçın Jun Yan Ji Zeng Arman Cohan Quanquan C. Liu | |||
 From Human-Level AI Tales to AI Leveling Human Scales Peter Romero Fernando Martínez-Plumed Zachary R. Tyler Matthieu Téhénan Sipeng Chen ...Yael Moros Daval Daniel Romero-Alvarado Félix Martí Pérez Kevin Wei José Hernández-Orallo | |||
 When LLM Judges Inflate Scores: Exploring Overrating in Relevance Assessment Chuting Yu Hang Li Guido Zuccon Joel Mackenzie Teerapong Leelanupab | |||
 References Improve LLM Alignment in Non-Verifiable Domains Kejian Shi Yixin Liu Peifeng Wang Alexander R. Fabbri Shafiq Joty Arman Cohan | |||
 ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders Ofer Meshi Krisztian Balog Sally Goldman Avi Caciularu Guy Tennenholtz Jihwan Jeong Amir Globerson Craig Boutilier | |||
 When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation Mubashara Akhtar Anka Reuel Prajna Soni Sanchit Ahuja Pawan Sasanka Ammanamanchi ...Mrinmaya Sachan Stella Biderman Zeerak Talat Avijit Ghosh Irene Solaiman | |||
 ResearchGym: Evaluating Language Model Agents on Real-World AI Research Aniketh Garikaparthi Manasi Patwardhan Arman Cohan | |||
 Who Do LLMs Trust? Human Experts Matter More Than Other LLMs Anooshka Bajaj Zoran Tiganj | |||
 Nanbeige4.1-3B: A Small General Model that Reasons, Aligns, and Acts Chen Yang Guangyue Peng Jiaying Zhu Ran Le Ruixiang Feng ...Yunzhi Xu Zekai Wang Zhenwei An Zhicong Sun Zongchao Chen | |||
 RankLLM: Weighted Ranking of LLMs by Quantifying Question Difficulty Ziqian Zhang Xingjian Hu Yue Huang Kai Zhang Ruoxi Chen ...Qingsong Wen Kaidi Xu Xiangliang Zhang Neil Zhenqiang Gong Lichao Sun | |||
 Gaia2: Benchmarking LLM Agents on Dynamic and Asynchronous Environments Romain Froger Pierre Andrews Matteo Bettini Amar Budhiraja Ricardo Silveira Cabral ...Mengjue Wang Ian Yu Amine Benhalloum Grégoire Mialon Thomas Scialom | |||
 Pedagogically-Inspired Data Synthesis for Language Model Knowledge Distillation Bowei He Yankai Chen Xiaokun Zhang Linghe Kong Philip S. Yu Xue Liu Chen Ma | |||
 Benchmark Illusion: Disagreement among LLMs and Its Scientific Consequences Eddie Yang Dashun Wang | |||
 Are Aligned Large Language Models Still Misaligned? Usman Naseem Gautam Siddharth Kashyap Rafiq Ali Ebad Shabbir Sushant Kumar Ray Abdullah Mohammad Agrima Seth | |||
 Scaling Reward Modeling without Human Supervision Jingxuan Fan Yueying Li Zhenting Qi Dinghuai Zhang Kianté Brantley Sham M. Kakade Hanlin Zhang | |||
 Fine-Tuning GPT-5 for GPU Kernel Generation Ali Tehrani Yahya Emara Essam Wissam Wojciech Paluch Waleed Atallah Łukasz Dudziak Mohamed S. Abdelfattah | |||
 Can Large Language Models Make Everyone Happy? Usman Naseem Gautam Siddharth Kashyap Ebad Shabbir Sushant Kumar Ray Abdullah Mohammad Rafiq Ali | |||
 FlexMoRE: A Flexible Mixture of Rank-heterogeneous Experts for Efficient Federatedly-trained Large Language Models Annemette Brok Pirchert Jacob Nielsen Mogens Henrik From Lukas Galke Poech Peter Schneider-Kamp | |||
 Whose Name Comes Up? Benchmarking and Intervention-Based Auditing of LLM-Based Scholar Recommendation Lisette Espin-Noboa Gonzalo Gabriel Mendez | |||
 InfiCoEvalChain: A Blockchain-Based Decentralized Framework for Collaborative LLM Evaluation Yifan Yang Jinjia Li Kunxi Li Puhao Zheng Yuanyi Wang Zheyan Qu Yang Yu Jianmin Wu Ming Li Hongxia Yang | |||
 When the Model Said Ño Comment', We Knew Helpfulness Was Dead, Honesty Was Alive, and Safety Was Terrified Gautam Siddharth Kashyap Mark Dras Usman Naseem | |||
 R-Align: Enhancing Generative Reward Models through Rationale-Centric Meta-Judging Yanlin Lai Mitt Huang Hangyu Guo Xiangfeng Wang Haodong Li ...Qi Han Chun Yuan Zheng Ge Xiangyu Zhang Daxin Jiang | |||
 AgentCPM-Explore: Realizing Long-Horizon Deep Exploration for Edge-Scale Agents Haotian Chen Xin Cong Shengda Fan Yuyang Fu Ziqin Gong ...Yukun Yan Zhong Zhang Yankai Lin Zhiyuan Liu Maosong Sun | |||
 SAIL: Self-Amplified Iterative Learning for Diffusion Model Alignment with Minimal Human Feedback Xiaoxuan He Siming Fu Wanli Li Zhiyuan Li Dacheng Yin Kang Rong Fengyun Rao Bo Zhang | |||
 Aligning Large Language Model Behavior with Human Citation Preferences Kenichiro Ando Tatsuya Harada | |||
 Scaling Agentic Verifier for Competitive Coding Zeyao Ma Jing Zhang Xiaokang Zhang Jiaxi Yang Zongmeng Zhang ...Lei Zhang Hao Zheng Wenting Zhao Junyang Lin Binyuan Hui | |||
 Aligning Language Model Benchmarks with Pairwise Preferences Marco Gutierrez Xinyi Leng Hannah Cyberey Jonathan Richard Schwarz Ahmed Alaa Thomas Hartvigsen | |||
 What LLMs Think When You Don't Tell Them What to Think About? Yongchan Kwon James Zou | |||
 Didactic to Constructive: Turning Expert Solutions into Learnable Reasoning Ethan Mendes Jungsoo Park Alan Ritter | |||
 PeerRank: Autonomous LLM Evaluation Through Web-Grounded, Bias-Controlled Peer Review Yanki Margalit Erni Avram Ran Taig Oded Margalit Nurit Cohen-Inger | |||
 Judging the Judges: Human Validation of Multi-LLM Evaluation for High-Quality K--12 Science Instructional Materials Peng He Zhaohui Li Zeyuan Wang Jinjun Xiong Tingting Li | |||
 CVeDRL: An Efficient Code Verifier via Difficulty-aware Reinforcement Learning Ji Shi Peiming Guo Meishan Zhang Miao Zhang Xuebo Liu Min Zhang Weili Guan | |||
 Why Self-Rewarding Works: Theoretical Guarantees for Iterative Alignment of Language Models Shi Fu Yingjie Wang Shengchao Hu Peng Wang Dacheng Tao | |||
 A Judge-Aware Ranking Framework for Evaluating Large Language Models without Ground Truth Mingyuan Xu Xinzi Tan Jiawei Wu Doudou Zhou | |||
 FineInstructions: Scaling Synthetic Instructions to Pre-Training Scale Ajay Patel Colin Raffel Chris Callison-Burch | |||
 ChipBench: A Next-Step Benchmark for Evaluating LLM Performance in AI-Aided Chip Design Zhongkai Yu Chenyang Zhou Yichen Lin Hejia Zhang Haotian Ye Junxia Cui Zaifeng Pan Jishen Zhao Yufei Ding | |||
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