Author

Sadid Hasan

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#artificial intelligence Preprint Sep 2026

Can We Trust LLM Judges: A Study of Capability-Dependent Biases and Multi-Judge Ensemble for Bias Calibration

LLMs are increasingly used as automated judges for model training and evaluation, yet individual judges exhibit systematic biases that undermine reliability. Much of prior work has studied biases in pairwise LLM-as-a-judge settings; in this paper, we focus on absolute scoring tasks, which mirror more realistic use case...

Gemma Zhang, Prachi Badarayani, Asmi Kumar et al. · 0 citations

#artificial intelligence Preprint Sep 2026

AIM: A Privacy-Aware Interoperable Memory Framework for Multi-Agent Multi-User LLM Systems

Traditional large language models (LLMs) are scoped to individual user sessions, limiting their knowledge to a single conversation and preventing them from learning user preferences that evolve over time. Existing agentic memory systems address this limitation but generally operate at the individual-user level, restric...

Zachary Johnson, Nigel Boachie Kumankumah, Somya Chatterjee et al. · 0 citations

Review Aug 2026

Metag: A dataset to build agentic meta-reviewing capabilities

Metag is a dataset to accelerate the development of meta-reviewing agents, specifically to identify changes made to scientific articles during the review-rebuttal process and will enable building methods to empower meta reviewers to quickly identify whether authors have addressed reviewer statements and where in the pa...

Anirudh S. Sundar, Min Chen, Divya Tadimeti et al. · 0 citations