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Human Feedback and Eval Paper Explorer

A focused feed for RLHF, preference data, rater protocols, agent evaluation, and LLM-as-judge research. Every paper includes structured metadata for quick triage.

Total papers: 216 Search mode: keyword RSS

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SkillCraft: Can LLM Agents Learn to Use Tools Skillfully?

Shiqi Chen, Jingze Gai, Ruochen Zhou, Jinghan Zhang, Tongyao Zhu, Junlong Li · Feb 28, 2026

Citations: 0
Automatic Metrics Long Horizon General
  • Real-world tool-using agents operate over long-horizon workflows with recurring structure and diverse demands, where effective behavior requires not only invoking atomic tools but also abstracting, and reusing higher-level tool…
  • Evaluating state-of-the-art agents on SkillCraft, we observe substantial efficiency gains, with token usage reduced by up to 80% by skill saving and reuse.
DARE-bench: Evaluating Modeling and Instruction Fidelity of LLMs in Data Science

Fan Shu, Yite Wang, Ruofan Wu, Boyi Liu, Zhewei Yao, Yuxiong He · Feb 27, 2026

Citations: 0
Automatic Metrics Long Horizon General
  • The fast-growing demands in using Large Language Models (LLMs) to tackle complex multi-step data science tasks create an emergent need for accurate benchmarking.
  • To bridge these gaps, we introduce DARE-bench, a benchmark designed for machine learning modeling and data science instruction following.
LFQA-HP-1M: A Large-Scale Human Preference Dataset for Long-Form Question Answering

Rafid Ishrak Jahan, Fahmid Shahriar Iqbal, Sagnik Ray Choudhury · Feb 27, 2026

Citations: 0
Pairwise PreferenceRubric Rating General
  • We present LFQA-HP-1M, a large-scale dataset comprising 1.3M human pairwise preference annotations for LFQA.
  • We propose nine rubrics for answer quality evaluation, and show that simple linear models based on these features perform comparably to state-of-the-art LLM evaluators.
Toward Expert Investment Teams:A Multi-Agent LLM System with Fine-Grained Trading Tasks

Kunihiro Miyazaki, Takanobu Kawahara, Stephen Roberts, Stefan Zohren · Feb 26, 2026

Citations: 0
Pairwise Preference Multi Agent General
  • While mainstream approaches deploy multi-agent systems mimicking analyst and manager roles, they often rely on abstract instructions that overlook the intricacies of real-world workflows, which can lead to degraded inference performance and…
  • Therefore, we propose a multi-agent LLM trading framework that explicitly decomposes investment analysis into fine-grained tasks, rather than providing coarse-grained instructions.
Risk-Aware World Model Predictive Control for Generalizable End-to-End Autonomous Driving

Jiangxin Sun, Feng Xue, Teng Long, Chang Liu, Jian-Fang Hu, Wei-Shi Zheng · Feb 26, 2026

Citations: 0
Demonstrations General
  • Practically, RaWMPC leverages a world model to predict the consequences of multiple candidate actions and selects low-risk actions through explicit risk evaluation.
  • Furthermore, to generate low-risk candidate actions at test time, we introduce a self-evaluation distillation method to distill riskavoidance capabilities from the well-trained world model into a generative action proposal network without…
Spatio-Temporal Token Pruning for Efficient High-Resolution GUI Agents

Zhou Xu, Bowen Zhou, Qi Wang, Shuwen Feng, Jingyu Xiao · Feb 26, 2026

Citations: 0
Automatic Metrics Web Browsing General
  • Pure-vision GUI agents provide universal interaction capabilities but suffer from severe efficiency bottlenecks due to the massive spatiotemporal redundancy inherent in high-resolution screenshots and historical trajectories.
  • We identify two critical misalignments in existing compression paradigms: the temporal mismatch, where uniform history encoding diverges from the agent's "fading memory" attention pattern, and the spatial topology conflict, where…
Citations: 0
Pairwise Preference General
  • Inspired by Humphrey's ipsundrum hypothesis, we implement ReCoN-Ipsundrum, an inspectable agent that extends a ReCoN state machine with a recurrent persistence loop over sensory salience Ns and an optional affect proxy reporting…
  • Across fixed-parameter ablations (ReCoN, Ipsundrum, Ipsundrum+affect), we operationalize Humphrey's qualiaphilia (preference for sensory experience for its own sake) as a familiarity-controlled scenic-over-dull route choice.
Decentralized Ranking Aggregation: Gossip Algorithms for Borda and Copeland Consensus

Anna Van Elst, Kerrian Le Caillec, Igor Colin, Stephan Clémençon · Feb 26, 2026

Citations: 0
Pairwise Preference Multi Agent General
  • The concept of ranking aggregation plays a central role in preference analysis, and numerous algorithms for calculating median rankings, often originating in social choice theory, have been documented in the literature, offering theoretical…
  • peer-to-peer networks, IoT, multi-agent systems), extending the ability to calculate consensus rankings with guarantees in a decentralized setting, i.e., when preference data is initially distributed across a communicating network, remains…
DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation

Hao Zheng, Guozhao Mo, Xinru Yan, Qianhao Yuan, Wenkai Zhang, Xuanang Chen · Feb 26, 2026

Citations: 0
Automatic Metrics Long Horizon General
  • However, existing presentation agents often rely on predefined workflows and fixed templates.
  • To address this, we present DeepPresenter, an agentic framework that adapts to diverse user intents, enables effective feedback-driven refinement, and generalizes beyond a scripted pipeline.
Moral Preferences of LLMs Under Directed Contextual Influence

Phil Blandfort, Tushar Karayil, Urja Pawar, Robert Graham, Alex McKenzie, Dmitrii Krasheninnikov · Feb 26, 2026

Citations: 0
Pairwise Preference General
  • Moral benchmarks for LLMs typically use context-free prompts, implicitly assuming stable preferences.
  • We introduce a pilot evaluation harness for directed contextual influence in trolley-problem-style moral triage: for each demographic factor, we apply matched, direction-flipped contextual influences that differ only in which group they…
Unleashing the Potential of Diffusion Models for End-to-End Autonomous Driving

Yinan Zheng, Tianyi Tan, Bin Huang, Enguang Liu, Ruiming Liang, Jianlin Zhang · Feb 26, 2026

Citations: 0
Simulation Env Long Horizon General
  • However, their applications and evaluations in autonomous driving remain limited to simulation-based or laboratory settings.
  • Moreover, we also provide an effective reinforcement learning post-training strategy to further enhance the safety of the learned planner.
AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications

Yujie Zhao, Boqin Yuan, Junbo Huang, Haocheng Yuan, Zhongming Yu, Haozhou Xu · Feb 26, 2026

Citations: 0
Automatic Metrics Long Horizon General
  • To bridge this gap, we introduce AMA-Bench (Agent Memory with Any length), which evaluates long-horizon memory for LLMs in real agentic applications.
  • To address these limitations, we propose AMA-Agent, an effective memory system featuring a causality graph and tool-augmented retrieval.
RLHFless: Serverless Computing for Efficient RLHF

Rui Wei, Hanfei Yu, Shubham Jain, Yogarajan Sivakumar, Devesh Tiwari, Jian Li · Feb 26, 2026

Citations: 0
Pairwise Preference Automatic Metrics General
  • Reinforcement Learning from Human Feedback (RLHF) has been widely applied to Large Language Model (LLM) post-training to align model outputs with human preferences.
Same Words, Different Judgments: Modality Effects on Preference Alignment

Aaron Broukhim, Nadir Weibel, Eshin Jolly · Feb 26, 2026

Citations: 0
Pairwise PreferenceRlaif Or Synthetic Feedback Automatic Metrics General
  • Preference-based reinforcement learning (PbRL) is the dominant framework for aligning AI systems to human preferences, but its application to speech remains underexplored.
  • We present a controlled cross-modal study of human and synthetic preference annotations, comparing text and audio evaluations of identical semantic content across 100 prompts.

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