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Si Li

Si Li has 3 papers in our library, in 2021–2026, most of them on Discourse analysis, Sentiment & emotion, Dialogue systems; often with Ji-Rong Wen, Jun Xu, Nianwen Xue.

3 papers in our library · 2021–2026

OpenAlex · ORCID · h-index 16 · 117 works · 965 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 45 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #7768

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. 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.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. Leveraging Generative Large Language Models with Visual Instruction and Demonstration Retrieval for Multimodal Sarcasm Detection (2024 · 33 citations)
    The paper addresses multimodal sarcasm detection: deciding whether an image–text post is sarcastic. Earlier systems fuse BERT/RoBERTa text features with visual features through elaborate custom networks. The authors argue that such networks tend to overfit their training domain and use cross-modal evidence poorly.…
  2. A Joint Model for Dropped Pronoun Recovery and Conversational Discourse Parsing in Chinese Conversational Speech (2021 · 16 citations)
    Chinese speakers frequently omit pronouns that listeners can infer from context. Existing systems handle two related problems separately: dropped pronoun recovery (DPR), which finds where a pronoun is missing and what type it is, and conversational discourse parsing (CDP), which links utterances through relations…
  3. ReContraster: Making Your Posters Stand Out with Regional Contrast (2026 · 2 citations)
    ReContraster addresses a gap in text-to-poster generation. Current systems produce tidy layouts and legible text, but their posters rarely grab attention at a glance. The authors build on the "contrast effects" idea from perception research: viewers react strongly to opposing stimuli, such as ruined versus green…

All works

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

  1. Guiding Generation for Abstractive Text Summarization Based on Key Information Guide Network ↗Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers) · no summary yetChenliang Li et al.2018 · 164 citations
  2. Linguistic Guidance for Sequence-to-Sequence AMR Parsing ↗Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference) · no summary yetBinghao Tang, Boda Lin, Si Li2024

 Co-authors here

3 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 45 times (of the 149,439 papers whose bibliographies we read); 8 citing papers with a page here →.

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