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Chen Gong

Chen Gong has 4 papers in our library, in 2024–2026, most of them on Language models & pretraining, Sentiment & emotion, Summarization; often with Guohong Fu, Han Hu, Indraneil Paul.

4 papers in our library · 2024–2026

OpenAlex · h-index 0 · 2 works · 0 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 153 times in our library · ⭐ Paper Stars ranking: #5883

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. BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions (2024 · 176 citations)
    Popular code benchmarks such as HumanEval and MBPP mostly test short, standalone algorithmic exercises, and recent models score near the top on them.
  2. SCAN: Structured Capability Assessment and Navigation for LLMs (2026 · 1 citation)
    Most automatic LLM benchmarks try to reproduce leaderboard orderings such as Chatbot Arena. They reveal little about where a particular model is strong or weak. SCAN (Structured Capability Assessment and Navigation) treats evaluation as a way to understand a model rather than to rank it.
  3. Locate and Explain: Joint Multimodal Emotion Cause Extraction and Summarization in Conversation (2026)
    Studies of why speakers feel emotions in multimodal dialogue usually take one of two approaches. Some pick out the utterances that trigger an emotion, which shows where the cause is but not what it is. Others write free-text cause descriptions, which explain the cause but cannot be traced to specific turns. The…
  4. Think Smart, Not Hard: Difficulty Adaptive Reasoning for Large Audio Language Models (2026)
    Large Audio Language Models (LALMs) that use chain-of-thought tend to apply the same reasoning depth to every question.

 Co-authors here

11 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 153 times (of the 149,439 papers whose bibliographies we read); 45 citing papers with a page here →.

Updated

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