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ToolLIFT: Lifting Tool-Specific Trajectories into Function-Level Graphs for Generalizable Tool Planning

简体中文

Core agent-mechanism mini-suite. Implements independent planning, memory, credit assignment, or topology paths and records process counts on deterministic tasks, not the full external environment.

Paper information

Field Details
Paper arXiv 2608.03468
Organization The authors do not disclose an affiliation
First public release 2026-08-04 (arXiv v1)
Authors' code No public author code was found as of 2026-08-24.
Adapter / method toollift
Local reproduction code src/auto_research/agent_research/historical_b10_b11.py
First author Xiuhui You

Original paper

Motivation and method

Lift tool-specific histories into a transferable function workflow graph and separate workflow planning from concrete tool selection.

flowchart LR
  O[Task and observation] --> P[Planning and state management]
  P --> M[ToolLIFT mechanism]
  M --> A[Actions and tools]
  A --> V[Verification and feedback]
  V --> P

Key figure from the paper

ToolLIFT: Lifting Tool-Specific Trajectories into Function-Level Graphs for Generalizable Tool Planning — Figure 2

Figure 2: Overall workflow, stages, and data flow. From the original paper; copyright remains with the authors.

Core equation

\[ G_F=Lift(\tau_{tool}),\quad tool_t=Select(f_t,s_t) \]

Paper results

It beats compared state-of-the-art methods across two in-domain and three out-of-domain benchmarks, particularly on unseen tool sets. These are paper results, not local mini-suite or online conclusions.

Local reproduction

On 120 planbench-mini episodes, ToolLIFT has joint success 1.0000 and mean cost 0.6100. The long-context control scores 1.0000 and costs 64.5000. With saturated success, inspect traces, source, and method-specific counts rather than inventing improvement. See the method metrics and batch index.

auto-research agent-research --method toollift --benchmark planbench-mini --episodes 120 --seed 42

Reproduction boundaries

The deterministic mini-suite does not access real browsers, AppWorld, SWE-bench, or external tool services. It verifies mechanism branches, intermediate states, and reporting contracts. Reproducing full environments requires the paper's resources. Raw runs are in runs/agent-research/; the repository keeps only metrics. See experiments.