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cs.CL2026
SIMMER: Benchmarking Latent Failures in LLM Executable Planning with a World Model
Xiaoxin Lu, Ranran Haoran Zhang, Rui Zhang
Large language models (LLMs) are increasingly deployed as planners for autonomous agents in household environments. While existing benchmarks evaluate whether LLM-generated plans e…
cs.AI2026
Bridging the Know-Act Gap via Task-Level Autoregressive Reasoning
Jihyun Janice Ahn, Ryo Kamoi, Berk Atil +34
LLMs often generate seemingly valid answers to flawed or ill-posed inputs. This is not due to missing knowledge: under discriminative prompting, the same models can mostly identify…