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From the 1 of 12 linked papers with an AI index.

collaborators

12 papers

cs.LG2026

EvolveNet: Collaborative Harness Evolution for Agent Self-Improvement

Jun Nie, Yonggang Zhang, Qianshu Cai +3

The capabilities of an LLM agent depend not only on its model but on the harness: the executable program that constructs context, invokes tools, verifies results, and recovers from…

cs.LG2026

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments

Jun Nie, Zhiqin Yang, Zhenheng Tang +4

Deep research agents increasingly operate over the open web, where relevant records coexist with redundant summaries, outdated reports, and misleading documents. Existing evaluatio…

cs.RO2026

Zero2Skill: Bootstrapping Robot Skills through Autonomous Data Collection, Training, and Deployment

Boyuan Wang, Zhenyuan Zhang, Zhiqin Yang +16

Zero2Skill is a robot learning system that autonomously collects, verifies, and resets manipulation data while using a large language model to store and reuse human corrections, dr…

cs.LG2026

A Control Theory of Predictability in Latent World Models

Hanzhe You, Yonggang Zhang, Maohao Ran +6

Latent world models are trained to predict future states in a learned representation and are then deployed inside a planner that selects actions by simulating them forward. Current…

cs.SE2026

TTHE: Test-Time Harness Evolution

Jun Nie, Yonggang Zhang, Jun Song +5

The behavior of an LLM agent is determined not only by the underlying model, but also by its harness: the executable program that constructs context, invokes tools, verifies interm…

cs.CL2026

Scaling Multi-Hop Training Data via Graph-Constrained Path Selection

Pengyu Chen, Yonggang Zhang, Mingming Chen +3

Endowing large language models with compositional reasoning over specialized documents requires multi-hop training data at scale, where such data rarely exists outside of curated b…