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20212026
most citedTowards Coherent Image Inpainting Using Denoising Diffusion Implicit Models

17 citations · 34 across the 20 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

cs.CL2026

Building AI Research Teams for Autonomous Discovery of Linear Attention Architectures

Yujian Liu, Li An, Zelin He +5

Autonomous agents can increasingly propose ideas, modify code, and run experiments, creating an opportunity to accelerate scientific discovery using teams of collaborative AI resea…

cs.AI2026

WorldAuditBench: Interactive 3D World Auditing with Multimodal Agents

Ziyan Jiang, Jingbo Yang, Jiabao Ji +5

As interactive 3D worlds are increasingly used to study intelligent behavior, it becomes important to develop efficient pipelines for identifying anomalies in these simulated envir…

cs.CL2026

Practical Online KV Cache Compaction for LLM Agents: An Empirical Study

Yujian Liu, Jiabao Ji, Li An +4

LLM agents accumulate long trajectories of reasoning steps, tool calls, and environment feedback, making the KV cache a major inference bottleneck. KV cache compaction can reduce t…

cs.AI2026

Speculate While You Reason: Teaching Agents to Predict Their Next Tool Call via Joint Agent-Speculator RL

Jiabao Ji, Yujian Liu, Li An +4

Large language model agents often spend substantial wall-clock time waiting for tool call results. Tool-call speculation can hide this latency by predicting and pre-executing an ag…

cs.CL2026

VISUALSKILL: Multimodal Skills for Computer-Use Agents

Ziyan Jiang, Li An, Yujian Liu +5

Computer-use agents (CUAs) approach human-level performance on standardised benchmarks but still struggle on long-horizon tasks and unseen software. Existing skill libraries addres…

cs.RO2026

Navigating the Clutter: Waypoint-Based Bi-Level Planning for Multi-Robot Systems

Jiabao Ji, Yongchao Chen, Yang Zhang +4

Multi-robot control in cluttered environments is a challenging problem that involves complex physical constraints, including robot-robot collisions, robot-obstacle collisions, and…

cs.CL2026★ 4 cited

How Well Do Agentic Skills Work in the Wild: Benchmarking LLM Skill Usage in Realistic Settings

Yujian Liu, Jiabao Ji, Li An +3

Agent skills, which are reusable, domain-specific knowledge artifacts, have become a popular mechanism for extending LLM-based agents, yet formally benchmarking skill usage perform…