8 papers
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…
Representation Alignment as a Bottleneck in LLM-Based Retrosynthesis Planning
Hyunwoo Yoo, Cassie Huang, Haebin Shin +2
While LLMs show promise in general reasoning, symbolic planning in chemistry remains a bottleneck. Direct ''SMILES-to-PDDL'' attempts fail because they force models to juggle chemi…
Robust Asynchronous Planning via Auto-Formalization
Jiayi Zhang, Jianing Yin, Ben Zhou +1
LLMs can plan by generating schedules directly as a Planner, or by translating a task into a formal specification for a solver as a Formalizer. Most real-world tasks are asynchrono…
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…
Language Model as Planner and Formalizer under Constraints
Cassie Huang, Stuti Mohan, Ziyi Yang +2
LLMs have been widely used in planning, either as planners to generate action sequences end-to-end, or as formalizers to represent the planning domain and problem in a formal langu…
Unifying Inference-Time Planning Language Generation
Prabhu Prakash Kagitha, Bo Sun, Ishan Desai +5
A line of work in planning uses LLM not to generate a plan, but to generate a formal representation in some planning language, which can be input into a symbolic solver to determin…
A Reality Check of Language Models as Formalizers on Constraint Satisfaction Problems
Rikhil Amonkar, Ceyhun Efe Kayan, Qimei Lai +2
Recent work shows superior performance when using large language models (LLMs) as formalizers instead of as end-to-end solvers for symbolic reasoning problems. Given the problem de…
On the Limit of Language Models as Planning Formalizers
Cassie Huang, Li Zhang
Large Language Models have been found to create plans that are neither executable nor verifiable in grounded environments. An emerging line of work demonstrates success in using th…