WebExpert: domain-aware web agents with critic-guided expert experience for high-precision search
arXiv cs.AI / 4/10/2026
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Key Points
- WebExpert is proposed as a domain-aware web agent for specialized search tasks in areas like finance and biomedicine, aiming to reduce query drift, noisy evidence, and brittle reasoning through domain priors.
- The system combines sentence-level experience retrieval with topic merging and rule distillation, plus a “schemalight” facet induction method that bootstraps time/region/policy/industry facets from weak supervision rather than hand-written lexicons.
- It uses preference-optimized planning that jointly improves query planning and retrieval via pairwise preference learning with a coverage-aware objective, and an inference-time experience gate that biases decoding toward relevant facets with fallback under low retrieval confidence.
- Experiments on GAIA, GPQA, HLE, and WebWalkerQA show Answer Exact Match improvements of 1.5–3.6 percentage points over the strongest browsing baseline and fewer page hops, with ablations supporting the contributions of each component.
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