3 papers
cs.AI2026
VeRA: Verified Reasoning Data Augmentation at Scale
Zerui Cheng, Jiashuo Liu, Chunjie Wu +4
The main issue with most evaluation schemes today is their "static" nature: the same problems are reused repeatedly, allowing for memorization, format exploitation, and eventual sa…
cs.AI2026
LPFQA: A Long-Tail Professional Forum-based Benchmark for LLM Evaluation
Liya Zhu, Peizhuang Cong, Jingzhe Ding +17
Large Language Models (LLMs) perform well on standard reasoning and question-answering benchmarks, yet such evaluations often fail to capture their ability to handle long-tail, exp…
cs.LG2025
LLM Swiss Round: Aggregating Multi-Benchmark Performance via Competitive Swiss-System Dynamics
Jiashuo Liu, Jiayun Wu, Chunjie Wu +5
The rapid proliferation of Large Language Models (LLMs) and diverse specialized benchmarks necessitates a shift from fragmented, task-specific metrics to a holistic, competitive ra…