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Xiangchen Song

Xiangchen Song has 2 papers in our library, in 2026, most of them on Language models & pretraining, Reasoning, Interpretability; often with Kun Zhang, Lingjing Kong, Aashiq Muhamed.

2 papers in our library · 2026

OpenAlex · h-index 11 · 35 works · 515 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 20 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #13182

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

🎓Carnegie Mellon UniversityPittsburgh · United States2021–2026 · 20 paperscurrent🎓University of Illinois Urbana-ChampaignUrbana · United States2020–2021 · 4 papers

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 5The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Interpretability · 1 workLanguage models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Mechanistic Interpretability Should Prioritize Feature Consistency in Sparse Autoencoders (2026 · 1 citation)
    Sparse autoencoders (SAEs) are a popular way to break LLM activations into sparse, human-readable features.
  2. Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards (2026)
    Masked diffusion language models (MdLLMs) such as LLaDA generate text by gradually unmasking a sequence. Reinforcement learning methods such as diffu-GRPO reward only the correctness of the final answer, so they do not supervise the denoising steps themselves. As a result, models often waste intermediate steps on…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation ↗Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations · no summary yetQingyun Wang et al.2021 · 140 citations
  2. Mechanistic Interpretability Should Prioritize Feature Consistency in Sparse AutoencodersAnnual Meeting of the Association for Computational Linguistics (ACL)Xiangchen Song, Aashiq Muhamed, Yujia Zheng, et al.2026 · 1 citation
  3. Advancing Reasoning in Diffusion Language Models with Denoising Process RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Shaoan Xie, Lingjing Kong, Xiangchen Song, et al.2026

 Co-authors here

8 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 20 times (of the 149,439 papers whose bibliographies we read).

Updated

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