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Haoliang Li

Haoliang Li has 4 papers in our library, in 2022–2026, most of them on Language models & pretraining, Sentiment & emotion, Information retrieval & search; often with Hui Liu, Wenya Wang, Chris Xing Tian.

4 papers in our library · 2022–2026

OpenAlex · ORCID · Wikidata · h-index 40 · 247 works · 6,462 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 32 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #6268

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. 38 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. Towards Multi-Modal Sarcasm Detection via Hierarchical Congruity Modeling with Knowledge Enhancement (2022 · 132 citations)
    The paper addresses multi-modal sarcasm detection: deciding whether a tweet and its attached image together convey sarcasm.
  2. Unraveling the Mechanics of Learning-Based Demonstration Selection for In-Context Learning (2025 · 11 citations)
    Retrievers trained to pick in-context learning demonstrations, such as EPR, beat simple heuristics like BM25 or off-the-shelf embeddings.
  3. Domain-Specific Data Generation Framework for RAG Adaptation (2026)
    Off-the-shelf RAG pipelines often perform poorly in specialised domains. Adapting their components, such as the embedding model or the generator LLM, requires domain-grounded training data, which is rarely available. The authors present RAGen, a data-centric framework that turns raw domain documents into…
  4. Task-Aware LLM Routing with Multi-Level Task-Profile-Guided Data Synthesis for Cold-Start Scenarios (2026)
    LLM routers pick a model from a candidate pool for each query, balancing answer quality against cost according to user preferences.

All works

6 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. Low-Light Image Enhancement with Normalizing Flow ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetYufei Wang et al.2022 · 536 citations

 Co-authors here

7 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 32 times (of the 149,439 papers whose bibliographies we read); 9 citing papers with a page here →.

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