repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago
Yuqi-Zhou/LRAT
The implementation for SIGIR 2026: Learning to Retrieve from Agent Trajectories.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 60%Self-Evolving World Models for LLM Agent Planning →
- PossiblePossibly related (embedding) · 57%Learning from Failure: Inference-Time Self-Improvement for Computer-Use Agents →
- PossiblePossibly related (embedding) · 57%SenseWalk: Agent-Based Semantic Trajectory Simulation Powered by Large Language Models in Zoned Environments →
- PossiblePossibly related (embedding) · 57%A field guide to AI agents in 2026 →
- PossiblePossibly related (embedding) · 56%Controllable Sim Agents with Behavior Latents →
- PossiblePossibly related (embedding) · 53%Doomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe Cascade →
- PossiblePossibly related (embedding) · 52%CurateEvo: Data-Curation Evolving for Agentic Post-Training →
- PossiblePossibly related (embedding) · 57%Demonstrating TOFFEE: A Learned System for Synthesizing Data Agent Trajectories at Scale →
Implements
paperSelf-Evolving World Models for LLM Agent PlanningpaperLearning from Failure: Inference-Time Self-Improvement for Computer-Use AgentspaperSenseWalk: Agent-Based Semantic Trajectory Simulation Powered by Large Language Models in Zoned EnvironmentspaperControllable Sim Agents with Behavior Latents
Related to
Implements (incoming)
Related across the graph
paperCurateEvo: Data-Curation Evolving for Agentic Post-TrainingpaperSelf-Evolving World Models for LLM Agent PlanningpaperControllable Sim Agents with Behavior LatentspaperSenseWalk: Agent-Based Semantic Trajectory Simulation Powered by Large Language Models in Zoned EnvironmentspaperDemonstrating TOFFEE: A Learned System for Synthesizing Data Agent Trajectories at ScalepaperLearning from Failure: Inference-Time Self-Improvement for Computer-Use AgentsarticleA field guide to AI agents in 2026paperDoomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe Cascade