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cs.AI2026
Planning Commitment of LLM under Partial Observability
Cassie Huang, Zhanwei Cao, Yeawon Lee +7
LLM-based planning agents commit to plans of different lengths before interacting with a partially observable environment. Some aggressively commit to a long plan based on assumpti…
cs.LG2026
Asymmetric Capacity Allocation in Self-Refinement Pipelines
Zhuoyi Yang, Ian G. Harris, Salar Hashemitaheri +7
Self-refinement, typically structured as generation, critique, and revision, is a widely adopted paradigm for improving LLM generation and serves as a core mechanism in many LLM ag…
cs.CL2026
Language Models as Higher-Order Planning Formalizers
Owen Jiang, Cassie Huang, Ashish Sabharwal +1
Recent work provides overwhelming evidence that LLMs, even those trained to scale their reasoning trace, quickly deteriorate at planning as problems become more complex. LLM-as-For…