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Xin Chen

Xin Chen has 6 papers in our library, in 2014–2026, most of them on Language models & pretraining, Dialogue systems, Evaluation & benchmarks; often with Jingang Wang, Du Su, Fei Sun.

6 papers in our library · 2014–2026

OpenAlex · h-index 0 · 6 works · 0 citations OpenAlex, 2026-10-14

📄 6 works in our library · 🔗 Cited 302 times in our library · ⭐ Paper Stars ranking: #3906

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

2010s

 Papers

The most cited first (OpenAlex and our library).

  1. InternLM2 Technical Report (2024 · 301 citations)
    Open-source LLMs still trail proprietary systems such as GPT-4, and earlier technical reports rarely explain how pre-training data was prepared.
  2. Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast (2022 · 133 citations)
    Numerical weather prediction (NWP) solves physical equations on supercomputers. It is slow, which limits timeliness and ensemble size, and its parameterizations introduce errors. Earlier deep learning forecasters such as FourCastNet were fast but less accurate than ECMWF's operational IFS.
  3. Automatic Assessment of the Speech of Young English Learners (2014 · 35 citations)
    The paper describes how Pearson automated the speaking section of AZELLA, Arizona's yearly English proficiency test for K-12 English learners.
  4. Too Consistent to Detect: A Study of Self-Consistent Errors in LLMs (2025 · 12 citations)
    LLM error detectors often treat agreement across sampled answers as a sign of correctness. This paper identifies a blind spot in that assumption: self-consistent errors , where a model gives the same wrong answer, up to semantic equivalence, in its greedy output and in all stochastic samples. The authors define these…
  5. BaseCal: Unsupervised Confidence Calibration via Base Model Signals (2026 · 1 citation)
    Post-trained LLMs (PoLLMs), such as instruction-tuned or RLHF-aligned models, tend to be overconfident: they assign high probability even to wrong answers, which limits the usefulness of confidence for detecting hallucinations.
  6. MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval Benchmarks (2026)
    Conversational retrieval decides which evidence a RAG system can use, but its benchmarks have two kinds of flaws.

 Co-authors here

12 of 29 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 302 times (of the 149,439 papers whose bibliographies we read); 75 citing papers with a page here →.

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