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Human Feedback and Eval Paper Explorer

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Total papers: 73 Search mode: keyword Shortlist (0) RSS

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Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 78% High protocol signal Freshness: Cold Status: Ready
Pairwise Preference Automatic Metrics Multi Agent General
  • While a multi-agent approach based on large language models (LLMs) represents a promising strategy to surpass the capabilities of single models, its success is critically dependent on synergistic team composition.
  • Priming conversations with specific topics identified synergistic teams which outperform random baselines on downstream benchmarks and achieve comparable accuracy to that of manually-curated teams based on known model specializations.
Open paper
Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models

Yubo Li, Xiaobin Shen, Xinyu Yao, Xueying Ding, Yidi Miao, Ramayya Krishnan · Apr 7, 2025

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 78% High protocol signal Freshness: Cold Status: Ready
Red Team Automatic Metrics MathCoding
  • We organize existing benchmarks and datasets into coherent categories reflecting the evolving landscape of multi-turn dialogue evaluation, and review a broad spectrum of enhancement methodologies, including model-centric strategies…
Open paper

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 78% Moderate protocol signal Freshness: Cold Status: Fallback
Simulation Env Multi Agent General
  • Human writers often begin their stories with an overarching mental scene, where they envision the interactions between characters and their environment.
  • Inspired by this creative process, we propose a novel approach to long-form story generation, termed hybrid bottom-up long-form story generation, using multi-agent simulations.
Open paper
LayerT2V: A Unified Multi-Layer Video Generation Framework

Guangzhao Li, Kangrui Cen, Baixuan Zhao, Yi Xin, Siqi Luo, Guangtao Zhai · Aug 6, 2025

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 78% Moderate protocol signal Freshness: Cold Status: Fallback
Automatic Metrics Long Horizon General
Open paper
Towards Hierarchical Multi-Step Reward Models for Enhanced Reasoning in Large Language Models

Teng Wang, Zhangyi Jiang, Zhenqi He, Shenyang Tong, Wenhan Yang, Yanan Zheng · Mar 16, 2025

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 78% High protocol signal Freshness: Cold Status: Fallback
Automatic Metrics Long Horizon MathLaw
  • Empirical results on the PRM800K dataset show that HRM, together with HNC, provides more stable and reliable evaluations than PRM.
  • Furthermore, cross-domain evaluations on the MATH500 and GSM8K datasets demonstrate HRM's strong generalization and robustness across a variety of reasoning tasks.
Open paper

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