most citedOverconfidence in LLM-as-a-Judge: Diagnosis and Confidence-Driven Solution

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Jev-ToM: Evaluating Theory of Mind in Typed Decision Models

Kawai Chung, Chunkit Chan, Yuxuan Liu +9

Dialogue and collaborative assistants repeatedly judge what a partner knows, believes, or intends. Typed decision models offer a potential alternative to generative large language…

cs.HC2026

GrandGuard: Taxonomy, Benchmark, and Safeguards for Elderly-Chatbot Interaction Safety

Changxuan Fan, Xi Yang, Yueyuan Zheng +9

As older adults increasingly use LLM-based chatbots for companionship and assistance, a safety gap is emerging. Older adults may face vulnerabilities from social isolation, limited…

cs.CL2026

QuantEval: A Benchmark for Financial Quantitative Tasks in Large Language Models

Zhaolu Kang, Junhao Gong, Wenqing Hu +15

Large Language Models (LLMs) have shown strong capabilities in finance-oriented question answering, yet their evaluation on professional quantitative workflows remains fragmented a…

cs.CR2025

GSPR: Aligning LLM Safeguards as Generalizable Safety Policy Reasoners

Haoran Li, Jingru Zeng, Yulin Chen +8

As large language models (LLMs) are integrated into numerous applications, LLMs' safety becomes critical for both application developers and intended users. Currently, great effort…

cs.AI2025★ 1 cited

Overconfidence in LLM-as-a-Judge: Diagnosis and Confidence-Driven Solution

Zailong Tian, Zhuoheng Han, Yanzhe Chen +5

Large Language Models (LLMs) are widely used as automated judges, where practical value depends on both accuracy and trustworthy, risk-aware judgments. Existing approaches predomin…