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From the 1 of 6 linked papers with an AI index.

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6 papers

physics.flu-dyn2026

DD-RNO: A Domain-Decomposed Routed Neural Operator for Airfoil Flow Prediction

T. A. Mehta, P. S. Bhati, H. D. Akolekar

Deep learning surrogates for RANS flow prediction around airfoils face two persistent bottlenecks. A single neural architecture cannot simultaneously resolve sharp near-wall bounda…

cs.CL2026

Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent

Lei Bai, Zongsheng Cao, Yang Chen +50

The paper introduces Agents-A1, a 35B mixture-of-experts agent model that attains trillion-parameter-level performance by extending the length of reasoning horizons and integrating…

cs.AI2026

MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery

Shangheng Du, Xiangchao Yan, Jinxin Shi +11

Large language model (LLM) agents are increasingly applied to long-horizon tasks such as scientific discovery and machine learning engineering (MLE), where sustained self-evolution…

cs.AI2026

A Survey on the Optimization of Large Language Model-based Agents

Shangheng Du, Jiabao Zhao, Jinxin Shi +4

With the rapid development of Large Language Models (LLMs), LLM-based agents have been widely adopted in various fields, becoming essential for autonomous decision-making and inter…

cs.AI2026

InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery

Shiyang Feng, Runmin Ma, Xiangchao Yan +53

We introduce InternAgent-1.5, a unified system designed for end-to-end scientific discovery across computational and empirical domains. The system is built on a structured architec…

cs.AI2025

AutoMLGen: Navigating Fine-Grained Optimization for Coding Agents

Shangheng Du, Xiangchao Yan, Dengyang Jiang +6

Large language models (LLMs) have shown impressive performance in general programming tasks. However, in Machine Learning Engineering (MLE) scenarios such as AutoML and Kaggle comp…