works on

From the 1 of 5 linked papers with an AI index.

collaborators

5 papers

cs.AI2026

MANTA: Multi-Agent Network Topology Adaptation for Self-Evolving Multi-Agent Systems

Mao-xun Huang, Jerry Wang, Yi-Cheng Lai +3

The paper presents MANTA, a framework that lets large language model‑driven multi‑agent systems dynamically adjust their communication topology during inference, updating roles, li…

cs.LG2026

HARP: Efficient Data Selection for Finetuning Large Language Models

Ning Wang, Zhengxin Zhang, Maosen Tang +3

Finetuning data selection requires balancing two competing goals: selecting examples that improve the downstream objective, and doing so without repeatedly finetuning models. Train…

cs.AI2026

How Far Are We From True Auto-Research?

Zhengxin Zhang, Ning Wang, Sainyam Galhotra +1

Recent auto-research systems can produce complete papers, but feasibility is not the same as quality, and the field still lacks a systematic study of how good agent-generated paper…

cs.CL2026

Bootstrapping Post-training Signals for Open-ended Tasks via Rubric-based Self-play on Pre-training Text

Chengyu Huang, Sheng-Yen Chou, Zhengxin Zhang +1

Self-play has recently emerged as a promising paradigm for post-training Large Language Models (LLMs). In self-play, the target LLM creates the task input (e.g., a question), which…

cs.CL2025

LLM Evaluation Based on Aerospace Manufacturing Expertise: Automated Generation and Multi-Model Question Answering

Beiming Liu, Zhizhuo Cui, Siteng Hu +3

Aerospace manufacturing demands exceptionally high precision in technical parameters. The remarkable performance of Large Language Models (LLMs), such as GPT-4 and QWen, in Natural…