Tuesday, October 27, 2026i10X News · Section desk9 stories
Studies
Benchmarks & Evals
New benchmarks, evaluation methods and leaderboard results
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Tampered ML: Even the Best AI Models Miss One in Five Planted Research Flaws
A new EMNLP 2026 benchmark pairs 1,858 ML experiment designs with flawed twins. Claude Opus 5 leads at 77.9%, but models flip verdicts when the order changes and favor polished flaws.
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Editor's picks
- Tampered ML: Even the Best AI Models Miss One in Five Planted Research Flaws
- Only One AI Agent Beats Researchers’ Own Code on Most FrontierCS 2 Tasks
- Hybrid Computer-Use Agents Top Out at 41% When GUI and CLI Must Work Together
- Scientific AI Agents Finish Only 21% of End-to-End Workflows — and Often Claim Success Anyway
- AI Agents Guess Wrong at Critical Forks 40% of the Time, Taste-Bench Shows
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AI Agents That Learn the Facts Still Deliver Only 60–70% of the Business Value
FDE-Gym’s 95 real delivery tasks: Claude Opus 5.5 leads at 0.56, but even models that gather 72–85% of key facts deliver just 0.60–0.70 of the reference…
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Best Video Model Scores Just 51% on Visual Reasoning Tasks, VGI-Bench Finds
VGI-Bench’s 27 tasks and 810 instances show video generators can do some visual reasoning, but Seedance 2.0 tops out at 51%, with almost no self-correction during…
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Agents’ Last Exam: Even Top Coding Agents Score Under 10% on the Hardest Tier
ALE holds 1,490 expert workflows; the best Codex+GPT-5.5 setup that scores 82% on Terminal-Bench gets under 10% on ALE’s hardest tier and 23.3% overall on ALE-CLI.
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