Research map / Large language models / Agents, code and math
Learning Combinatory Categorial Grammars for Plan Recognition
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| increase noise (dropped actions) in training traces from 0 to 25 percent | LEXlearn · Logistics | F1 | No clear effect |
Closest papers by meaning
- Learning Planning Abstractions from Language (ICLR 2024 · similarity 0.82)
- Symbolic Numeric Planning with Patterns (AAAI 2024 · similarity 0.81)
- Learning Planning Domains from Non-redundant Fully-Observed Traces: Theoretical Foundations and Complexity Analysis (AAAI 2024 · similarity 0.81)
- PlanLLM: Video Procedure Planning with Refinable Large Language Models (AAAI 2025 · similarity 0.80)
- System 1.x: Learning to Balance Fast and Slow Planning with Language Models (ICLR 2025 · similarity 0.80)
- Large Language Models as Planning Domain Generators (Student Abstract) (AAAI 2024 · similarity 0.80)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
