HFEPX Fortnight Archive: 2026-F02

Updated from current HFEPX corpus (Feb 27, 2026). This page tracks 27 papers for HFEPX Fortnight Archive: 2026-F02. Dominant protocol signals include automatic metrics, simulation environments, human evaluation, with frequent benchmark focus on Retrieval, DocVQA and metric focus on f1, latency. Use the grounded sections below to prioritize reproducible protocol choices, benchmark-matched comparisons, and judge-vs-human evaluation checks.

Papers Published On This Date

• Decoupling Strategy and Execution in Task-Focused Dialogue via Goal-Oriented Preference Optimization

  Jingyi Xu, Xingyu Ren, Zhoupeng Shou, Yumeng Zhang, Zhiqiang You · Jan 24, 2026

  Pairwise Preference Long Horizon

  Large language models show potential in task-oriented dialogue systems, yet existing training methods often rely on token-level likelihood or preference optimization, which poorly align with long-horizon task success.

• Building Safe and Deployable Clinical Natural Language Processing under Temporal Leakage Constraints

  Ha Na Cho, Sairam Sutari, Alexander Lopez, Hansen Bow, Kai Zheng · Jan 24, 2026

  Such behavior poses substantial risks for real-world deployment, where overconfident or temporally invalid predictions can disrupt clinical workflows and compromise patient safety.

• Large Language Models as Automatic Annotators and Annotation Adjudicators for Fine-Grained Opinion Analysis

  Gaurav Negi, MA Waskow, John McCrae, Paul Buitelaar · Jan 23, 2026

  Although this level of detail is sound, it requires considerable human effort and substantial cost to annotate opinions in datasets for training models, especially across diverse domains and real-world applications.

• PhysE-Inv: A Physics-Encoded Inverse Modeling approach for Arctic Snow Depth Prediction

  Akila Sampath, Vandana Janeja, Jianwu Wang · Jan 23, 2026

  The accurate estimation of Arctic snow depth remains a critical time-varying inverse problem due to the scarcity in associated sea ice parameters.

• Between Search and Platform: ChatGPT Under the DSA

  Toni Lorente, Kathrin Gardhouse · Jan 22, 2026

  Web Browsing

  This article examines the applicability of the Digital Services Act (DSA) to ChatGPT, arguing that it should be classified as a hybrid of the two types of hosting services: online search engines and platforms.

• ErrorMap and ErrorAtlas: Charting the Failure Landscape of Large Language Models

  Shir Ashury-Tahan, Yifan Mai, Elron Bandel, Michal Shmueli-Scheuer, Leshem Choshen · Jan 22, 2026

  Large Language Models (LLM) benchmarks tell us when models fail, but not why they fail.

• RebuttalAgent: Strategic Persuasion in Academic Rebuttal via Theory of Mind

  Zhitao He, Zongwei Lyu, Yi R Fung · Jan 22, 2026

  Pairwise PreferenceCritique Edit

  In this paper, we introduce RebuttalAgent, the first framework to ground academic rebuttal in Theory of Mind (ToM), operationalized through a ToM-Strategy-Response (TSR) framework that models reviewer mental state, formulates persuasion str

• APEX-Agents

  Bertie Vidgen, Austin Mann, Abby Fennelly, John Wright Stanly, Lucas Rothman · Jan 20, 2026

  Rubric RatingExpert Verification Long Horizon

  We introduce the AI Productivity Index for Agents (APEX-Agents), a benchmark for assessing whether AI agents can execute long-horizon, cross-application tasks created by investment banking analysts, management consultants, and corporate law

• Human Values in a Single Sentence: Moral Presence, Hierarchies, and Transformer Ensembles on the Schwartz Continuum

  Víctor Yeste, Paolo Rosso · Jan 20, 2026

  We study sentence-level detection of the 19 human values in the refined Schwartz continuum in about 74k English sentences from news and political manifestos (ValueEval'24 corpus).

• Chain-of-Thought Compression Should Not Be Blind: V-Skip for Efficient Multimodal Reasoning via Dual-Path Anchoring

  Dongxu Zhang, Yiding Sun, Cheng Tan, Wenbiao Yan, Ning Yang · Jan 20, 2026

  While Chain-of-Thought (CoT) reasoning significantly enhances the performance of Multimodal Large Language Models (MLLMs), its autoregressive nature incurs prohibitive latency constraints.

• When LLMs Imagine People: A Human-Centered Persona Brainstorm Audit for Bias and Fairness in Creative Applications

  Hongliu Cao, Eoin Thomas, Rodrigo Acuna Agost · Jan 19, 2026

  Existing methods rely on constrained tasks and fixed benchmarks, leaving open-ended creative outputs unexamined.

• Multimodal Multi-Agent Empowered Legal Judgment Prediction

  Zhaolu Kang, Junhao Gong, Qingxi Chen, Hao Zhang, Jiaxin Liu · Jan 19, 2026

  Multi Agent

  Furthermore, we build JurisMM, a large dataset with over 100,000 recent Chinese judicial records, including both text and multimodal video-text data, enabling comprehensive evaluation.

• Orthogonalized Policy Optimization:Policy Optimization as Orthogonal Projection in Hilbert Space

  Wang Zixian · Jan 18, 2026

  Long Horizon

  Experiments on MATH benchmarks show that the Hilbert projection formulation prevents gradient saturation typical of KL-constrained methods.

• Event Detection with a Context-Aware Encoder and LoRA for Improved Performance on Long-Tailed Classes

  Abdullah Al Monsur, Nitesh Vamshi Bommisetty, Gene Louis Kim · Jan 17, 2026

  The current state of event detection research has two notable re-occurring limitations that we investigate in this study.

• Generating metamers of human scene understanding

  Ritik Raina, Abe Leite, Alexandros Graikos, Seoyoung Ahn, Dimitris Samaras · Jan 16, 2026

  Human vision combines low-resolution "gist" information from the visual periphery with sparse but high-resolution information from fixated locations to construct a coherent understanding of a visual scene.

• Toward Ultra-Long-Horizon Agentic Science: Cognitive Accumulation for Machine Learning Engineering

  Xinyu Zhu, Yuzhu Cai, Zexi Liu, Bingyang Zheng, Cheng Wang · Jan 15, 2026

  Long Horizon

  The advancement of artificial intelligence toward agentic science is currently bottlenecked by the challenge of ultra-long-horizon autonomy, the ability to sustain strategic coherence and iterative correction over experimental cycles spanni

• AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers

  Prachuryya Kaushik, Ashish Anand · Jan 15, 2026

  We introduce \textbf{AWED-FiNER}, an open-source collection of agentic tool, web application, and 53 state-of-the-art expert models that provide Fine-grained Named Entity Recognition (FgNER) solutions across 36 languages spoken by more than

• Alignment Pretraining: AI Discourse Causes Self-Fulfilling (Mis)alignment

  Cameron Tice, Puria Radmard, Samuel Ratnam, Andy Kim, David Africa · Jan 15, 2026

  We share our models, data, and evaluations at AlignmentPretraining.ai.

• Context Volume Drives Performance: Tackling Domain Shift in Extremely Low-Resource Translation via RAG

  David Samuel Setiawan, Raphaël Merx, Jey Han Lau · Jan 15, 2026

  Qualitative analysis confirms the LLM acts as a robust "safety net," repairing severe failures in zero-shot domains.

• Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning

  Chi-Pin Huang, Yunze Man, Zhiding Yu, Min-Hung Chen, Jan Kautz · Jan 14, 2026

  Pairwise Preference Long Horizon

  Fast-ThinkAct learns to reason efficiently with latent CoTs by distilling from a teacher, driven by a preference-guided objective to align manipulation trajectories that transfers both linguistic and visual planning capabilities for embodie

• CLiMB: A Domain-Informed Novelty Detection Clustering Framework for Galactic Archaeology and Scientific Discovery

  Lorenzo Monti, Tatiana Muraveva, Brian Sheridan, Davide Massari, Alessia Garofalo · Jan 14, 2026

  In data-driven scientific discovery, a challenge lies in classifying well-characterized phenomena while identifying novel anomalies.

• CAST: Character-and-Scene Episodic Memory for Agents

  Kexin Ma, Bojun Li, Yuhua Tang, Liting Sun, Ruochun Jin · Jan 14, 2026

  Episodic memory is a central component of human memory, which refers to the ability to recall coherent events grounded in who, when, and where.

• A Parallel Cross-Lingual Benchmark for Multimodal Idiomaticity Understanding

  Dilara Torunoğlu-Selamet, Dogukan Arslan, Rodrigo Wilkens, Wei He, Doruk Eryiğit · Jan 13, 2026

  Pairwise Preference

  The dataset, containing 34 languages and over ten thousand items, allows comparative analyses of idiomatic patterns among language-specific realisations and preferences in order to gather insights about shared cultural aspects.

• FigEx2: Visual-Conditioned Panel Detection and Captioning for Scientific Compound Figures

  Jifeng Song, Arun Das, Pan Wang, Hui Ji, Kun Zhao · Jan 12, 2026

  To support high-quality supervision, we curate BioSci-Fig-Cap, a refined benchmark for panel-level grounding, alongside cross-disciplinary test suites in physics and chemistry.

• VULCA-Bench: A Multicultural Vision-Language Benchmark for Evaluating Cultural Understanding

  Haorui Yu, Diji Yang, Hang He, Fengrui Zhang, Qiufeng Yi · Jan 12, 2026

  Critique Edit

  We introduce VULCA-Bench, a multicultural art-critique benchmark for evaluating Vision-Language Models' (VLMs) cultural understanding beyond surface-level visual perception.

• Cross-Cultural Expert-Level Art Critique Evaluation with Vision-Language Models

  Haorui Yu, Xuehang Wen, Fengrui Zhang, Qiufeng Yi · Jan 12, 2026

  Rubric RatingCritique Edit

  Existing benchmarks assess perception without interpretation, and common evaluation proxies, such as automated metrics and LLM-judge averaging, are unreliable for culturally sensitive generative tasks.

• Reward Modeling from Natural Language Human Feedback

  Zongqi Wang, Rui Wang, Yuchuan Wu, Yiyao Yu, Pinyi Zhang · Jan 12, 2026

  Pairwise PreferenceCritique Edit

  Reinforcement Learning with Verifiable reward (RLVR) on preference data has become the mainstream approach for training Generative Reward Models (GRMs).

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