The authors define a candidate pool as all documents made available to an agent for an evaluation question.
Correcting search bias makes deep research conclusions more representative
A probability-based audit reduced errors caused by agents selectively reading documents from a defined evidence pool.
Academic
Shuyao Xiao · Shengling Wang · Xuan Chen · Ke Chao · Ming Cui · Feifei Qian · +5 more
Beijing Normal University · Ke Holdings
Research Digest··3 min read
Xiao and colleagues treat an agent’s search process as adaptive evidence sampling, where early results influence later queries, document choices and stopping.
Why this paper
From Beijing Normal University and Ke Holdings
In one line
CESS corrects evidence selection bias in deep research agents by weighting documents by their selection probabilities.
What we could check
- ·No code link found
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ✓Limitations stated by the authors
- ✓Reports numbers on named benchmarks (2 benchmarks)
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
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