Signals 4 · free daily AI digest

ProteinGeoBench: Frontier Structural-Biology Agents Are Fluent at Lookup but Lost in Geometry

Paper recorded by Signals 4 on 2026-10-19 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-19 on arXiv · recorded by Signals 4 on 2026-10-20

Category: cs.AI · 人工智能 · first seen 2026-10-20

Abstract

Frontier agents retrieve structural metadata well and compute geometry from coordinates less reliably. We ask how much of a benchmark score reflects that gap and how much reflects the evaluation configuration around the model. We study ProteinGeoBench, a suite of 131 protein-structure tasks, using 4,249 rollouts from four frontier models and 4,486 further trials across 26 models. Three of the four

Read on arXiv →

#251 most recent of 960 cs.AI papers we have recorded · ↑ newer: Kronecker Delta Rule for Long Context Linear Attention · ↓ older: Agent World Model in the Wild: Computer-Use Agent Environment Synthesi
Cite this page: ProteinGeoBench: Frontier Structural-Biology Agents Are Fluent at Lookup but Lost in Geometry: the #251 most recent of 960 cs.AI papers we have recorded (as of 2026-10-19). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/proteingeobench-frontier-structural-biology-agents-are-fluent-at-lookup-but-lost.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.AI papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions