works on

From the 1 of 36 linked papers with an AI index.

most citedACON: Optimizing Context Compression for Long-horizon LLM Agents

1 citations · 1 across the 9 of their papers we have counts for

collaborators

36 papers

cs.AI2026

AutoSaddler: Automatic Harness Optimization with Durable Updates from Agent Execution Traces

Sungho Park, Wonjoong Kim, Rongyuan Tan +10

LLM agents remain unreliable on long-horizon tasks, where small local failures can compound over extended interactions and lead to overall task failure. Although external harnesses…

cs.SE2026

LoopsBench: From Harness Engineering to Loop Engineering in Coding Agent Evaluation

Han Li, Zhemin Fang, Rili Feng +8

Coding agent infrastructure is shifting from harness engineering toward loop engineering as coding agents are deployed for sustained long-horizon software development. Existing ben…

cs.SE2026

Change2Task: From Repository Changes to Executable Coding Agent Tasks and Environments

Haomin Qi, Xingliang Wang, Xuanqi Gao +9

The paper introduces Change2Task, a system that turns merged pull requests from software repositories into verified, executable coding‑agent tasks by reconstructing the code state…

cs.SE2026

DepRepair: LLM-Based Source-Code Repair for Dependency Breaking Changes

Shenghao Yang, Bo Lu, Yaochen Liu +5

Modern software projects depend on numerous third-party libraries, whose updates often introduce breaking changes. Adapting consumer code to such changes remains labor-intensive an…

cs.SE2026

AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation

Chenyu Zhao, Shenglin Zhang, Wenwei Gu +5

Large language model (LLM) agents are increasingly used for multi-step, stateful tool-use tasks, yet production reliability remains limited. Unlike static software repair, agent re…

cs.AI2026

Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity

Menglin Xia, Xuchao Zhang, Shantanu Dixit +6

Agent memory systems must accommodate continuously growing information while supporting efficient, context-aware retrieval for downstream tasks. Abstraction is essential for scalin…