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Tian Wang

Tian Wang has 3 papers in our library, in 2026, most of them on Language models & pretraining, Code & programming languages, Efficient models & compression; often with Jiri Gesi, Bing Yin, Dakuo Wang.

3 papers in our library · 2026

OpenAlex · ORCID · h-index 6 · 21 works · 195 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 13 times in our library · ⭐ Paper Stars ranking: #9437

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

🔬Beijing Orient Institute of Measurement and TestBeijing · China2017–2026 · 4 paperscurrent🎓Harbin University of Science and TechnologyHarbin · China2017–2021 · 6 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 more institutions on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksArtificial Intelligence · 3 worksInformation Systems · 2 worksArts and Humanities · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 2 worksCode & programming languages · 1 workEfficient models & compression · 1 work

 Works by year

2020s

20263 papers

 Papers

The most cited first (OpenAlex and our library).

  1. OPeRA: A Dataset of Observation, Persona, Rationale, and Action for Evaluating LLMs on Human Online Shopping Behavior Simulation (2026 · 8 citations)
    LLM agents can produce plausible web behavior, but it is hard to check whether they reproduce what a specific person would actually do.
  2. CODERL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment (2026 · 5 citations)
    LLMs learn code by predicting text, but whether a program is correct depends on how it behaves when run. RLVR methods try to close this gap by rewarding programs that pass tests. A single pass/fail bit, however, gives little guidance about subtle logic errors such as mistracked loop variables.
  3. On-Policy Self-Distillation for Efficient Diffusion Language Models with Early-Stage Calibration (2026 · 2 citations)
    Diffusion language models such as masked diffusion models (MDMs) decode many tokens in parallel. Their first decoding steps are unreliable because almost every position is still masked. Those early errors carry forward, lowering output quality. They also force the model to unmask only a few tokens per step, which…

 Co-authors here

12 of 15 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 13 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated

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