HFEPX Weekly Archive: 2026-W04

Updated from current HFEPX corpus (Feb 27, 2026). This page tracks 12 papers for HFEPX Weekly Archive: 2026-W04. Dominant protocol signals include automatic metrics, human evaluation, simulation environments, with frequent benchmark focus on DocVQA, Lawbench and metric focus on accuracy, agreement. 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.

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