Search

3 results for “WebShop”

1. Research · Reinforcement learning

   AI agents complete more multistep tasks by reusing related experience

   BLPO: Beyond-Local Policy Optimization for Long-Horizon LLM Agents

   Across two simulated environments and two model sizes, the authors report higher task success when training reuses evidence about useful actions across tasks and training updates.

   WebShop: 74.02% Task Success (as reported)

   3 Nov 2026Beihang University, Alibaba Group

2. Research · Agents

   RL method helps AI agents learn high-level task strategies from sparse rewards

   TalentRL: Strategy-Guided Reinforcement Learning for Hierarchical Skill Routing

   A hierarchical reinforcement learning approach separates strategy selection from skill execution to improve routing credit assignment.

   WebShop: 90.7 average score (as reported)

   2 Nov 2026Microsoft AI

3. Research · Agents

   AI web agents learn long tasks by reusing skills salvaged from failures

   From Local Skills to Long-Horizon Web Tasks: Progressive Skill Exploration for LLM Web Agents

   A training loop that extracts reusable sub-skills from unsuccessful web-browsing trajectories, stitches them into longer skill chains, and distils the results back into the model improved task success by 3.9% to 18.6% over the strongest baselines.

   WebShop: 0.93 reward (as reported)

   3 Nov 2026Renmin University of China, Huawei Technologies