most citedMeasuring Agents in Production

3 citations · 4 across the 11 of their papers we have counts for

collaborators

12 papers

cs.SE2026

DeployBench: Benchmarking LLM Agents for Research Artifact Deployment

Yuanli Wang, Yaoyao Qian, Yue Zhang +8

LLM agents have made rapid progress on software engineering and ML research tasks, but these advances often assume access to a working runnable environment. For research artifacts…

cs.AI2026

OpenDeepThink: Parallel Reasoning via Bradley-Terry Aggregation

Shang Zhou, Wenhao Chai, Kaiyuan Liu +3

Test-time compute scaling is a primary axis for improving LLM reasoning. Existing methods primarily scale depth by extending a single reasoning trace. Scaling breadth by sampling m…

cs.CL2026

Concurrency without Model Changes: Future-based Asynchronous Function Calling for LLMs

Guangyu Feng, Huanzhi Mao, Prabal Dutta +1

Function calling, also known as tool use, is a core capability of modern LLM agents but is typically constrained by synchronous execution semantics. Under these semantics, LLM deco…

cs.LG2026

FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale

Runyuan He, Qiuyang Mang, Shang Zhou +14

Many real-world coding challenges are open-ended and admit no known optimal solution. Yet, recent progress in LLM coding has focused on well-defined tasks such as feature implement…

cs.CV2026

SVG-EAR: Parameter-Free Linear Compensation for Sparse Video Generation via Error-aware Routing

Xuanyi Zhou, Qiuyang Mang, Shuo Yang +7

Diffusion Transformers (DiTs) have become a leading backbone for video generation, yet their quadratic attention cost remains a major bottleneck. Sparse attention reduces this cost…

cs.CL2026

ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders

Ofer Meshi, Krisztian Balog, Sally Goldman +5

The promise of LLM-based user simulators to improve conversational AI is hindered by a critical "realism gap," leading to systems that are optimized for simulated interactions, but…