20 citations · 46 across the 42 of their papers we have counts for
6 papers · 1 filter
Geometric Calibration of Supervised Fine-Tuning
Jianzhu Bao, Jia-Chen Gu, Qingyuan Liu +4
Recent studies investigate the weight geometry through its spectral structure, which characterizes how the weights transform different input directions. Within this view, supervise…
Overwhelmed by Choice: Studying LLM Decision Making at Scale
Yu-Chi Lin, Aryan Seth, Anshul Aravind +4
Multiple-choice and candidate-selection evaluations are widely used to assess LLM reasoning and decision-making, yet most benchmarks contain relatively small candidate sets. It rem…
OpenVLThinkerV2: A Generalist Multimodal Reasoning Model for Multi-domain Visual Tasks
Wenbo Hu, Xin Chen, Yan Gao-Tian +3
Group Relative Policy Optimization (GRPO) has emerged as the de facto Reinforcement Learning (RL) objective driving recent advancements in Multimodal Large Language Models. However…
Beyond Facts: Benchmarking Distributional Reading Comprehension in Large Language Models
Pei-Fu Guo, Ya-An Tsai, Chun-Chia Hsu +6
While most reading comprehension benchmarks for LLMs focus on factual information that can be answered by localizing specific textual evidence, many real-world tasks require unders…
SemEval-2026 Task 3: Dimensional Aspect-Based Sentiment Analysis (DimABSA)
Liang-Chih Yu, Jonas Becker, Shamsuddeen Hassan Muhammad +14
We present the SemEval-2026 shared task on Dimensional Aspect-Based Sentiment Analysis (DimABSA), which improves traditional ABSA by modeling sentiment along valence-arousal (VA) d…
TaoBench: Do Automated Theorem Prover LLMs Generalize Beyond MathLib?
Alexander K Taylor, Junyi Zhang, Ethan Ji +10
Automated theorem proving (ATP) benchmarks largely consist of problems formalized in MathLib, so current ATP training and evaluation are heavily biased toward MathLib's definitiona…