Showing cs.CLShow all
3 papers · 1 filter
cs.CL2026
PDDL-Mind: Large Language Models are Capable on Belief Reasoning with Reliable State Tracking
Wang Bill Zhu, Qiutong Tony Yi, Robin Jia +1
Large language models (LLMs) perform substantially below human level on existing theory-of-mind (ToM) benchmarks, even when augmented with chain-of-thought prompting or probabilist…
cs.CL2025
Large Language Models Do Multi-Label Classification Differently
Marcus Ma, Georgios Chochlakis, Niyantha Maruthu Pandiyan +2
Multi-label classification is prevalent in real-world settings, but the behavior of Large Language Models (LLMs) in this setting is understudied. We investigate how autoregressive…
cs.CL2024
When Parts Are Greater Than Sums: Individual LLM Components Can Outperform Full Models
Ting-Yun Chang, Jesse Thomason, Robin Jia
This paper studies in-context learning by decomposing the output of large language models into the individual contributions of attention heads and MLPs (components). We observe cur…