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Total papers: 438 Search mode: keyword Shortlist (0) RSS

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When AI Meets Early Childhood Education: Large Language Models as Assessment Teammates in Chinese Preschools

Xingming Li, Runke Huang, Yanan Bao, Yuye Jin, Yuru Jiao, Qingyong Hu · Mar 25, 2026

Citations: 0

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

Score: 90% High protocol signal Freshness: Hot Status: Ready
Rubric Rating Automatic Metrics General
  • In this paper, we investigate whether AI can serve as a scalable assessment teammate by extracting structured quality indicators and validating their alignment with human expert judgments.
  • Our contributions include: (1) TEPE-TCI-370h (Tracing Effective Preschool Education), the first large-scale dataset of naturalistic teacher-child interactions in Chinese preschools (370 hours, 105 classrooms) with standardized ECQRS-EC and…
Open paper
Prompt Attack Detection with LLM-as-a-Judge and Mixture-of-Models

Hieu Xuan Le, Benjamin Goh, Quy Anh Tang · Mar 26, 2026

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 45% Moderate protocol signal Freshness: Hot Status: Ready
Red Team Llm As Judge General
  • In production, guardrails must mitigate these attacks under strict low-latency constraints, resulting in a deployment gap in which lightweight classifiers and rule-based systems struggle to generalize under distribution shift, while…
  • In this work, we examine whether lightweight, general-purpose LLMs can reliably serve as security judges under real-world production constraints.
Open paper
OneSearch-V2: The Latent Reasoning Enhanced Self-distillation Generative Search Framework

Ben Chen, Siyuan Wang, Yufei Ma, Zihan Liang, Xuxin Zhang, Yue Lv · Mar 25, 2026

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 45% Moderate protocol signal Freshness: Hot Status: Ready
Pairwise Preference Automatic Metrics General
  • However, its inadequate understanding of complex queries, inefficient exploitation of latent user intents, and overfitting to narrow historical preferences have limited its further performance improvement.
  • It contains three key innovations: (1) a thought-augmented complex query understanding module, which enables deep query understanding and overcomes the shallow semantic matching limitations of direct inference; (2) a reasoning-internalized…
Open paper

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