2 citations · 2 across the 10 of their papers we have counts for
10 papers
When Your Agent Opens the Chat App: Agent-Controlled Search over Raw Chat Logs Rivals Structured Memory
Ruizhe Li, Licheng Zhang, Benfeng Xu +3
Agent-memory systems increasingly buy retrieval quality with structure, transforming raw conversation histories into summaries, embeddings, trees, or knowledge graphs before any qu…
Beyond Borrowed Histories: Person-Aligned User Simulation for Interactive Role-Playing Evaluation
Yuhang Zhu, Mingxuan Du, Benfeng Xu +3
Role-playing agents (RPAs) have become one of the most important consumer applications of large language models. Users engage in multi-turn conversations with RPAs for experiences…
MPIE-Bench: Benchmarking Anatomically Plausible Multi-Person Interaction Editing
Jiajia Lin, Mingxuan Du, Tuowen Zhou +2
Text-to-image and personalized editing models now synthesize high-fidelity single-subject images with ease. Yet placing multiple named people into shared contact actions such as em…
Keep It InMind: Benchmarking the Implicit-Association Blind Spot in Agent Memory
Ruizhe Li, Mingxuan Du, Benfeng Xu +1
Long-term memory systems store what a user says in an external store and retrieve it when a related query arrives. This interface rests on an assumption so natural that it is rarel…
A-RAG: Scaling Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces
Mingxuan Du, Benfeng Xu, Chiwei Zhu +4
Frontier language models have demonstrated strong reasoning and long-horizon tool-use capabilities. However, existing RAG systems fail to leverage these capabilities. They still re…
WildGraphBench: Benchmarking GraphRAG with Wild-Source Corpora
Pengyu Wang, Benfeng Xu, Licheng Zhang +4
Graph-based Retrieval-Augmented Generation (GraphRAG) organizes external knowledge as a hierarchical graph, enabling efficient retrieval and aggregation of scattered evidence acros…
Wiki Live Challenge: Challenging Deep Research Agents with Expert-Level Wikipedia Articles
Shaohan Wang, Benfeng Xu, Licheng Zhang +5
Deep Research Agents (DRAs) have demonstrated remarkable capabilities in autonomous information retrieval and report generation, showing great potential to assist humans in complex…
FS-Researcher: Test-Time Scaling for Long-Horizon Research Tasks with File-System-Based Agents
Chiwei Zhu, Benfeng Xu, Mingxuan Du +4
Deep research is emerging as a representative long-horizon task for large language model (LLM) agents. However, long trajectories in deep research often exceed model context limits…
DeepResearch Bench II: Diagnosing Deep Research Agents via Rubrics from Expert Reports
Ruizhe Li, Mingxuan Du, Benfeng Xu +3
Deep Research Agents (DRA) aim to help users search the web, synthesize information, and deliver comprehensive investigative reports. Prior benchmarks often either under-evaluate a…
DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents
Mingxuan Du, Benfeng Xu, Chiwei Zhu +2
Deep Research Agents are a prominent category of LLM-based agents. By autonomously orchestrating multistep web exploration, targeted retrieval, and higher-order synthesis, they tra…