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20242026
most citedUniMate: A Unified Model for Mechanical Metamaterial Generation, Property Prediction, and Condition Confirmation

1 citations · 1 across the 15 of their papers we have counts for

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cs.AI2026

Small but Mighty: Test Suites as Improvement Signals for Self-Evolving Agents

Yutong Cheng, Wei Cheng, Wenchao Yu +2

A self-evolving agent rewrites its own harness and must decide which rewrites to keep, so its improvement signal is the check a rewrite has to pass. Verifying a rewrite by agent ro…

cs.AI2026

ForkPilot: Self-Evolving Policy for Retrospective Search in Long-Horizon Agents

Xinyue Zeng, Shivam Shandilya, Guilherme Potje +6

Interactive language-model agents increasingly solve complex tasks through long-horizon, multi-call reasoning, where errors in beliefs or actions can compound across tool interacti…

cs.AI2026

The Emerging AI Paper-Review Arms Race: Adversarial Co-Evolution in Scholarly Publishing

Chenguang Wang, Ming Li, Adebayo Braimah +6

Generative and agentic AI are reshaping both the production and evaluation of scientific research. These developments are often studied separately, as questions of how AI can produ…

cs.AI2026

Think Again or Think Longer? Selective Verification for Budget-Aware Reasoning

Sajib Acharjee Dip, Dawei Zhou, Liqing Zhang

Test-time reasoning is increasingly used as a serving-time control knob, but extra reasoning is not uniformly valuable: it can repair failed attempts, waste compute on already-corr…

cs.AI2026

METASYMBO: Multi-Agent Language-Guided Metamaterial Discovery via Symbolic Latent Evolution

Jianpeng Chen, Wangzhi Zhan, Dongqi Fu +5

Metamaterial discovery seeks microstructured materials whose geometry induces targeted mechanical behavior. Existing inverse-design methods can efficiently generate candidates, but…

cs.AI2025

MatSciBench: Benchmarking the Reasoning Ability of Large Language Models in Materials Science

Junkai Zhang, Jingru Gan, Xiaoxuan Wang +8

Large Language Models have shown strong scientific reasoning ability, but their performance on materials science problems remains less studied. To fill this gap, we introduce MatSc…

cs.AI2024

MetaScientist: A Human-AI Synergistic Framework for Automated Mechanical Metamaterial Design

Jingyuan Qi, Zian Jia, Minqian Liu +15

The discovery of novel mechanical metamaterials, whose properties are dominated by their engineered structures rather than chemical composition, is a knowledge-intensive and resour…

cs.AI2024

Rethinking the Uncertainty: A Critical Review and Analysis in the Era of Large Language Models

Mohammad Beigi, Sijia Wang, Ying Shen +9

In recent years, Large Language Models (LLMs) have become fundamental to a broad spectrum of artificial intelligence applications. As the use of LLMs expands, precisely estimating…