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Escaping the Cognitive Well: Efficient Competition Math with Off-the-Shelf Models

An inference pipeline using off-the-shelf models and conjecture extraction with context detachment achieves state-of-the-art IMO-style math performance at much lower cost by escaping the Cognitive Well.

Xingyu Dang, Rohit Agarwal, Rodrigo Porto, Anirudh Goyal and 2 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 2/5
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The Alien Space of Science: Sampling Coherent but Cognitively Unavailable Research Directions

A framework samples coherent but cognitively unavailable "alien" research directions by maximizing idea coherence while minimizing existing community availability, broadening explored vocabularies 3.5-7x over LLM baselines.

Alejandro H. Artiles, Martin Weiss, Levin Brinkmann, Iyad Rahwan and 5 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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13/20 AI panelreviewers recommend it

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 1/5
88%Must read
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FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics

FML-bench isolates agent strategy from infrastructure across 18 ML tasks, finding greedy hill-climbing nearly matches tree search, while adaptive exploration switching outperforms fixed strategies.

Qiran Zou, Hou Hei Lam, Wenhao Zhao, Tingting Chen and 10 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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15/20 AI panelreviewers recommend it

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AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 1/5