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The Tasteful Agent: Measuring and Improving Taste in Long-Horizon Tasks research paper by Microsoft, 2026

Microsoft · Sep 22, 2026 · Agents and evaluation · 0 citations · 119 upvotes · unverified

Read on arXiv

What it shows

LLM agents increasingly work on long-horizon tasks, and the decisions they make along the way, such as which hypothesis to test or which implementation to build on, determine the outcome of the whole run.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Wenbo Pan, Zhichao Liu, Shujie Liu and 6 more
arXiv
2609.25804 · PDF
Citations
0, 0 influential · Semantic Scholar
Upvotes
119 · Hugging Face
Code
github.com/wbopan/tastebench
Lab
Microsoft · on Companies · on Acquisitions · on Quarterly · on Paydays · on Releases · on TechConf

Changes

What changed
Upvotes118 to 119 (+1)Sep 25, 2026
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 0Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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