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Siheng Chen

Siheng Chen has 6 papers in our library, in 2025–2026, most of them on Evaluation & benchmarks; often with WenHao Wang, Guangyi Liu, Pengxiang Zhao.

6 papers in our library · 2025–2026

OpenAlex · h-index 1 · 7 works · 1 citations OpenAlex, 2026-10-14

📄 6 works in our library · 🔗 Cited 29 times in our library · ⭐ Paper Stars ranking: #8254

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Shanghai Jiao Tong UniversityShanghai · China2025–2026 · 5 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 6 worksComputer Science · 6 worksArtificial Intelligence · 6 worksLanguage and Linguistics · 6 worksHuman-Computer Interaction · 2 worksComputer Networks and Communications · 1 workComputer Science Applications · 1 work

🧭 Topics 1Research subjects and languages the work is about.Evaluation & benchmarks · 1 work

 Works by year

2020s

20265 papers20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Synthesizing Post-Training Data for LLMs through Multi-Agent Simulation (2025 · 19 citations)
    Post-training turns base LLMs into instruction followers, but it needs high-quality instruction data. Such data is expensive to annotate, scarce, and often limited by privacy. Existing synthetic approaches such as Self-Instruct, WizardLM and Magpie usually produce instructions that are not tied to any realistic user…
  2. LearnAct: Few-Shot Mobile GUI Agent with a Unified Demonstration Benchmark (2026 · 9 citations)
    Mobile GUI agents built on large language models often fail in rare, app-specific situations that pre-training or fine-tuning cannot fully cover.
  3. MCP-Flow: Facilitating LLM Agents to Master Real-World, Diverse and Scaling MCP Tools (2026 · 7 citations)
    LLM agents increasingly need to work with tools exposed through the Model Contextual Protocol (MCP), but even strong models handle real MCP servers poorly.
  4. FedGUI: Benchmarking Federated GUI Agents across Heterogeneous Platforms, Devices, and Operating Systems (2026)
    GUI agents built on vision–language models usually depend on centrally gathered, manually labelled interaction data, which is expensive and hard to scale.
  5. TeachMaster: Generative Teaching via Code (2026)
    Producing online course videos by hand is costly and slow; typical courses cost around $30,000. Pixel-level video generators such as Sora 2 are expensive to run, hard to edit, and weak on pedagogical structure. The authors propose "Generative Teaching," in which educators act as directors who state teaching goals…
  6. Text2Mem: A Unified Memory Operation Language for Memory Operating System (2026)
    LLM agents that work across long, multi-session interactions need memory. Yet current memory frameworks mostly offer basic create/read/delete-style primitives. Higher-level controls such as merging, promoting, locking or expiring memories are absent or implemented differently from system to system. Text2Mem addresses…

 Co-authors here

12 of 21 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 29 times (of the 149,439 papers whose bibliographies we read); 13 citing papers with a page here →.

Updated

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