43 citations · 129 across the 62 of their papers we have counts for
71 papers
FOCUS: Training-Free Decision-Preserving Context Compression for LLM Agents
Shantanu Dixit, Anson Bastos, Xuchao Zhang +2
LLM agents accumulate interaction histories that grow linearly with task length, causing quadratic inference cost scaling and performance degradation from attention dilution. Exist…
PSD: Pseudo Self-Distillation of Memory Representation Capabilities for LLM Agents
Pirzada Suhail, Menglin Xia, Xuchao Zhang +3
Memory systems are becoming a core component of LLM agents, but constructing and maintaining memory remains expensive because it relies on repeated calls to large proprietary langu…
When EOS Tokens Disagree: Understanding Length Inflation in On-Policy Distillation
Yuxiao Yang, Tianrun Yu, Shangzhe Li +6
We study length inflation in on-policy distillation (OPD), where student responses can become excessively long and even exhaust the generation budget. We identify \emph{termination…
A Resource-centric Analysis and Optimization of NoSQL Workloads using Distressed Resource Volume Metric
Gunika Verma, Aashutosh A, Pooja Srinivas +9
Large-scale managed cloud databases leverage sophisticated load Packing and Migration (PAM) algorithms, which provide the efficiencies necessary for running these services at scale…
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…
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…
Debugging the Debuggers: Failure-Anchored Structured Recovery for Software Engineering Agents
Chenyu Zhao, Shenglin Zhang, Yihang Lin +7
Software engineering agents are increasingly deployed in evaluable engineering environments, yet post-failure recovery remains costly, manual, and ad hoc. Existing systems expose t…
EvidenT: An Evidence-Preserving Framework for Iterative System-Level Package Repair
Chenyu Zhao, Minghua Ma, Shenglin Zhang +5
Frequent toolchain updates and growing ISA diversity have made system-level software package repair increasingly important. Diagnosing and repairing build failures remains challeng…
ActionNex: A Virtual Outage Manager for Cloud Computing
Zhenfeng Lin, Haoji Hu, Ming Hao +11
Outage management in large-scale cloud operations remains heavily manual, requiring rapid triage, cross-team coordination, and experience-driven decisions under partial observabili…
WebXSkill: Skill Learning for Autonomous Web Agents
Zhaoyang Wang, Qianhui Wu, Xuchao Zhang +12
Autonomous web agents powered by large language models (LLMs) remain brittle on long-horizon browser workflows. A key bottleneck is a grounding gap in existing skill formulations:…
AutoAdapt: An Automated Domain Adaptation Framework for LLMs
Sidharth Sinha, Anson Bastos, Xuchao Zhang +3
Large language models (LLMs) excel in open domains but struggle in specialized settings with limited data and evolving knowledge. Existing domain adaptation practices rely heavily…
Provable and Practical In-Context Policy Optimization for Self-Improvement
Tianrun Yu, Yuxiao Yang, Zhaoyang Wang +6
We study test-time scaling, where a model improves its answer through multi-round self-reflection at inference. We introduce In-Context Policy Optimization (ICPO), in which an agen…
A Holistic Framework for Automated Configuration Recommendation for Cloud Service Monitoring
Anson Bastos, Shreeya Venneti, Anjaly Parayil +3
Reliability of large-scale cloud services is critical for user satisfaction and business continuity. Despite significant investments in reliability engineering, production incident…
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…
AgentRx: Diagnosing AI Agent Failures from Execution Trajectories
Shraddha Barke, Arnav Goyal, Alind Khare +3
AI agents often fail in ways that are difficult to localize because executions are probabilistic, long-horizon, multi-agent, and mediated by noisy tool outputs. We address this gap…
Your Self-Play Algorithm is Secretly an Adversarial Imitator: Understanding LLM Self-Play through the Lens of Imitation Learning
Shangzhe Li, Xuchao Zhang, Chetan Bansal +1
Self-play post-training methods has emerged as an effective approach for finetuning large language models and turn the weak language model into strong language model without prefer…
A Benchmark for Language Models in Real-World System Building
Weilin Jin, Chenyu Zhao, Zeshun Huang +12
During migration across instruction set architectures (ISAs), software package build repair is a critical task for ensuring the reliability of software deployment and the stability…
Sutradhara: An Intelligent Orchestrator-Engine Co-design for Tool-based Agentic Inference
Anish Biswas, Kanishk Goel, Srivarshinee S +5
Agentic applications are LLMs that iteratively invoke external tools to accomplish complex tasks. Such tool-based agents are rapidly becoming the dominant paradigm for deploying la…
Serving Heterogeneous LoRA Adapters in Distributed LLM Inference Systems
Shashwat Jaiswal, Shrikara Arun, Anjaly Parayil +8
Low-Rank Adaptation (LoRA) has become the de facto method for parameter-efficient fine-tuning of large language models (LLMs), enabling rapid adaptation to diverse domains. In prod…
Generative Caching for Structurally Similar Prompts and Responses
Sarthak Chakraborty, Suman Nath, Xuchao Zhang +2
Large Language Models (LLMs) are increasingly being used to plan, reason, and execute tasks across diverse scenarios. In use cases like repeatable workflows and agentic settings, p…
Continuous Benchmark Generation for Evaluating Enterprise-scale LLM Agents
Divyanshu Saxena, Rishikesh Maurya, Xiaoxuan Ou +7
The rapid adoption of AI agents across domains has made systematic evaluation crucial for ensuring their usefulness and successful production deployment. Evaluation of AI agents ty…
Triage in Software Engineering: A Systematic Review of Research and Practice
Yongxin Zhao, Shenglin Zhang, Yujia Wu +5
As modern software systems continue to grow in complexity, triage has become a fundamental process in system operations and maintenance. Triage aims to efficiently prioritize, assi…
SynthAgent: Adapting Web Agents with Synthetic Supervision
Zhaoyang Wang, Yiming Liang, Xuchao Zhang +9
Web agents struggle to adapt to new websites due to the scarcity of environment specific tasks and demonstrations. Recent works have explored synthetic data generation to address t…
Can Language Models Go Beyond Coding? Assessing the Capability of Language Models to Build Real-World Systems
Chenyu Zhao, Shenglin Zhang, Zeshun Huang +8
Large language models (LLMs) have shown growing potential in software engineering, yet few benchmarks evaluate their ability to repair software during migration across instruction…