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Yifan Yang

Yifan Yang has 5 papers in our library, in 2023–2026, most of them on Language models & pretraining, Efficient models & compression; often with Bang Zhang, Fanghua Ye, Haoqin Sun.

5 papers in our library · 2023–2026

OpenAlex · h-index 0 · 7 works · 0 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 58 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #5407

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

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.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Information (2023 · 223 citations)
    Large language models often invent facts when asked about precise database content, such as gene aliases, SNP positions or sequence alignments. Commercial search engines rarely index this kind of knowledge. GeneGPT addresses the problem by letting Codex (code-davinci-002) query the NCBI Web APIs directly.
  2. Sentient Agent as a Judge: Evaluating Higher-Order Social Cognition in Large Language Models (2026 · 6 citations)
    Standard LLM leaderboards reward textual skill and helpfulness, but they rarely check whether a model actually reads people well.
  3. SpeechLLM-as-Judges: Towards General and Interpretable Speech Quality Evaluation (2026 · 3 citations)
    Judging how good synthetic speech sounds is still difficult. Common tools such as MOS ratings, A/B tests, or MCD produce a single number or a binary choice, which explains nothing about the judgment. Learned predictors such as UTMOS are usually limited to one task and one language. The authors propose…
  4. FLAT-LLM: Fine-grained Low-rank Activation Space Transformation for Large Language Model Compression (2026 · 2 citations)
    Large language models are costly to run on limited hardware. Low-rank compression helps, but SVD-based variants often lose accuracy, need recovery fine-tuning, and split layers into two smaller matrix multiplications that run poorly on GPUs. SliceGPT avoids SVD but adds adapters on residual paths, which costs memory.…
  5. From Mimesis to Metamorphosis: Evolving VLM Judges via In-Context Comparing and Knowledge Internalization (2026)
    VLM-based judges that output absolute scores for subjective qualities such as aesthetics tend to be unreliable.

All works

7 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

  1. Towards Fine-Grained and Multi-Granular Contrastive Language-Speech Pre-training ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetYifan Yang et al.2026
  2. ToolCPT: Improving Tool Utilization in LLM Agents via Continuous Pre-training ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetYifan Yang et al.2026

 Co-authors here

12 of 24 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 58 times (of the 149,439 papers whose bibliographies we read); 21 citing papers with a page here →.

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