activity
20172026
most citedTowards Efficiently Evaluating the Robustness of Deep Neural Networks in IoT Systems: A GAN-based Method

9 citations · 20 across the 9 of their papers we have counts for

collaborators

12 papers

cs.CL2026

DuoDiscover: Scaling Autonomous Discovery Beyond the Evaluation Bottleneck

Shubham Agarwal, Akshat Gupta, Mike Heddes +21

Evaluation has been central to advances in AI, and it is equally critical to autonomous discovery. Yet scaling autonomous discovery to real-world engineering challenges faces a fun…

cs.AI2026

Harmony Harness: Multi-Objective Self-Evolution of Agent Harnesses

Weichen Yu, Lesly Miculicich, Bhavana Dalvi Mishra +5

Recent work on self-evolving LLM agents treats the agent harness as an optimization target that can be iteratively improved through execution feedback. Existing approaches, however…

cs.AI2026

AIM: Agentic Idea Management for Automated Research

Hyeong Kyu Choi, Bhavana Dalvi Mishra, Jiefeng Chen +7

Frontier LLMs are increasingly used to automate scientific research through iterative search. We distinguish idea-driven search from solution-driven search and identify three core…

cs.AI2026

AutoLab: Can Frontier Models Solve Long-Horizon Auto Research and Engineering Tasks?

Zhangchen Xu, Junda Chen, Yue Huang +16

Scientific and engineering progress is fundamentally a long-horizon iterative process: proposing changes, running experiments, measuring outcomes, and continuously refining artifac…

cs.SE2026

T2J-BENCH: Benchmarking Coding Agents on Execution-Grounded PyTorch-to-JAX Repository Migration

Tao Feng, Linxin Song, Jiefeng Chen +9

Migrating a machine-learning codebase across frameworks--for example from PyTorch to JAX--is a routine but costly engineering task that is fundamentally cross-paradigm: eager, stat…

cs.AI2026

ScientistOne: Towards Human-Level Autonomous Research via Chain-of-Evidence

Rui Meng, Bhavana Dalvi Mishra, Jiefeng Chen +10

Autonomous research agents produce competitive solutions and professional-looking manuscripts, yet their outputs contain verifiability failures undetectable by surface-level evalua…