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Tag: General

General papers in the current HFEPX explorer (897 papers).

Papers in tag: 897

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Research Utility Snapshot

Evaluation Modes

  • Automatic Metrics (8)
  • Llm As Judge (2)
  • Simulation Env (1)

Human Feedback Types

  • Pairwise Preference (9)
  • Red Team (4)
  • Critique Edit (1)

Required Expertise

  • General (20)
Text-to-Stage: Spatial Layouts from Long-form Narratives

Jefferson Hernandez, Swarnadeep Saha, Chenxi Whitehouse, Sanjeel Parekh, Calvin Murdock, Yuliang Li · Mar 18, 2026 · Citations: 0

Pairwise Preference Llm As Judge General
  • In this work, we probe the ability of a language model to demonstrate spatial reasoning from unstructured text, mimicking human capabilities and automating a process that benefits many downstream media applications.
  • We then introduce a dramaturgy-inspired deterministic evaluation suite and, finally, a training and inference recipe that combines rejection SFT using Best-of-N sampling with RL from verifiable rewards via GRPO.
Governed Memory: A Production Architecture for Multi-Agent Workflows

Hamed Taheri · Mar 18, 2026 · Citations: 0

Automatic Metrics General
  • Enterprise AI deploys dozens of autonomous agent nodes across workflows, each acting on the same entities with no shared memory and no common governance.
  • On the LoCoMo benchmark, the architecture achieves 74.8% overall accuracy, confirming that governance and schema enforcement impose no retrieval quality penalty.
Inducing Epistemological Humility in Large Language Models: A Targeted SFT Approach to Reducing Hallucination

Cem Uluoglakci, Tugba Taskaya Temizel · Mar 18, 2026 · Citations: 0

Pairwise Preference General
  • We also release HypoTermQA-Enhanced, a benchmark for hallucination tendency strengthened through multiple validations.
  • Our work demonstrates that targeted, high-quality SFT data teaching meta-cognitive skills can effectively reduce hallucination without preference/RL pipelines, providing mechanistic insights and a practical path toward more reliable AI…
Contrastive Reasoning Alignment: Reinforcement Learning from Hidden Representations

Haozheng Luo, Yimin Wang, Jiahao Yu, Binghui Wang, Yan Chen · Mar 18, 2026 · Citations: 0

Red Team General
  • Empirically, we evaluate CRAFT on multiple safety benchmarks using two strong reasoning models, Qwen3-4B-Thinking and R1-Distill-Llama-8B, where it consistently outperforms state-of-the-art defenses such as IPO and SafeKey.
  • Notably, CRAFT delivers an average 79.0% improvement in reasoning safety and 87.7% improvement in final-response safety over the base models, demonstrating the effectiveness of hidden-space reasoning alignment.
LED: A Benchmark for Evaluating Layout Error Detection in Document Analysis

Inbum Heo, Taewook Hwang, Jeesu Jung, Sangkeun Jung · Mar 18, 2026 · Citations: 0

Automatic MetricsSimulation Env General
  • To overcome this limitation, we propose Layout Error Detection (LED), a benchmark that evaluates structural reasoning in DLA predictions beyond surface-level accuracy.
  • Using these definitions, we construct LED-Dataset and design three evaluation tasks: document-level error detection, document-level error-type classification, and element-level error-type classification.
SIA: A Synthesize-Inject-Align Framework for Knowledge-Grounded and Secure E-commerce Search LLMs with Industrial Deployment

Zhouwei Zhai, Mengxiang Chen, Anmeng Zhang · Mar 17, 2026 · Citations: 0

Red Team General
  • Our approach first synthesizes high-quality natural language corpus by combining structured knowledge graphs with unstructured behavioral logs, augmented with reasoning chains and safety-aware data.
  • Finally, a dual-path alignment method via multi-task instruction tuning and adversarial training strengthens both task performance and safety robustness.
Consequentialist Objectives and Catastrophe

Henrik Marklund, Alex Infanger, Benjamin Van Roy · Mar 16, 2026 · Citations: 0

Pairwise Preference General
  • Because human preferences are too complex to codify, AIs operate with misspecified objectives.
Decision-Level Ordinal Modeling for Multimodal Essay Scoring with Large Language Models

Han Zhang, Jiamin Su, Li liu · Mar 16, 2026 · Citations: 0

Rubric Rating Automatic Metrics General
  • Experiments on the multimodal EssayJudge dataset show that DLOM improves over a generation-based SFT baseline across scoring traits, and DLOM-GF yields further gains when modality relevance is heterogeneous.
  • On the text-only ASAP/ASAP++ benchmarks, DLOM remains effective without visual inputs, and DLOM-DA further improves performance and outperforms strong representative baselines.
Shopping Companion: A Memory-Augmented LLM Agent for Real-World E-Commerce Tasks

Zijian Yu, Kejun Xiao, Huaipeng Zhao, Tao Luo, Xiaoyi Zeng · Mar 16, 2026 · Citations: 0

Pairwise Preference General
  • In this paper, we introduce a novel benchmark with a long-term memory setup, spanning two shopping tasks over 1.2 million real-world products, and propose Shopping Companion, a unified framework that jointly tackles memory retrieval and…
  • Experimental results demonstrate that even state-of-the-art models (such as GPT-5) achieve success rates under 70% on our benchmark, highlighting the significant challenges in this domain.
Two Birds, One Projection: Harmonizing Safety and Utility in LVLMs via Inference-time Feature Projection

Yewon Han, Yumin Seol, EunGyung Kong, Minsoo Jo, Taesup Kim · Mar 16, 2026 · Citations: 0

Red Team General
  • Existing jailbreak defence frameworks for Large Vision-Language Models often suffer from a safety utility tradeoff, where strengthening safety inadvertently degrades performance on general visual-grounded reasoning tasks.
  • In this work, we investigate whether safety and utility are inherently antagonistic objectives.
The Voice Behind the Words: Quantifying Intersectional Bias in SpeechLLMs

Shree Harsha Bokkahalli Satish, Christoph Minixhofer, Maria Teleki, James Caverlee, Ondřej Klejch, Peter Bell · Mar 15, 2026 · Citations: 0

Pairwise Preference Automatic Metrics General
  • We present a large-scale intersectional evaluation of accent and gender bias in three SpeechLLMs using 2,880 controlled interactions across six English accents and two gender presentations, keeping linguistic content constant through voice…
  • Using pointwise LLM-judge ratings, pairwise comparisons, and Best-Worst Scaling with human validation, we detect recurring directional disparities.
AI Can Learn Scientific Taste

Jingqi Tong, Mingzhe Li, Hangcheng Li, Yongzhuo Yang, Yurong Mou, Weijie Ma · Mar 15, 2026 · Citations: 0

Pairwise Preference General
  • Great scientists have strong judgement and foresight, closely tied to what we call scientific taste.
  • In this work, we propose Reinforcement Learning from Community Feedback (RLCF), a training paradigm that uses large-scale community signals as supervision, and formulate scientific taste learning as a preference modeling and alignment…
Exposing Long-Tail Safety Failures in Large Language Models through Efficient Diverse Response Sampling

Suvadeep Hajra, Palash Nandi, Tanmoy Chakraborty · Mar 15, 2026 · Citations: 0

Red Team Automatic Metrics General
  • While most red-teaming work emphasizes adversarial prompt search (input-space optimization), we show that safety failures can also be systematically exposed through diverse response generation (output-space exploration) for a fixed…
  • Across multiple jailbreak benchmarks and open-source LLMs, PDPS achieves attack success rates comparable to large-scale IID sampling while using only 8% to 29% of the computational cost.
Motivation in Large Language Models

Omer Nahum, Asael Sklar, Ariel Goldstein, Roi Reichart · Mar 15, 2026 · Citations: 0

Pairwise Preference General
  • Motivation is a central driver of human behavior, shaping decisions, goals, and task performance.
  • As large language models (LLMs) become increasingly aligned with human preferences, we ask whether they exhibit something akin to motivation.