6 papers
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…
Robust Asynchronous Planning via Auto-Formalization
Jiayi Zhang, Jianing Yin, Ben Zhou +1
LLMs can plan by either generating action sequences directly as a Planner or translating tasks into domain specific language for an external solver as a Formalizer. While most real…
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…
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…
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…
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…