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Ayesha Qamar

Ayesha Qamar has 2 papers in our library, in 2023–2025, most of them on Speech act theory, Dialogue systems, Language models & pretraining; often with Ruihong Huang, Adarsh Pyarelal.

2 papers in our library · 2023–2025

OpenAlex · h-index 5 · 19 works · 375 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 9 times in our library · ⭐ Paper Stars ranking: #9776

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

🎓Army Medical CollegeRawalpindi · Pakistan2017–2026 · 3 paperscurrent🎓Superior UniversityLahore · Pakistan2026 · 1 papercurrent🏥Osmania General HospitalHyderabad · India1992–2020 · 6 papers🎓Texas A&M UniversityCollege Station · United States2024–2025 · 3 papers🎓National University of Medical SciencesRawalpindi · Pakistan2017 · 2 papers

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.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 4Research subjects and languages the work is about.Dialogue systems · 2 worksSpeech act theory · 2 worksEnglish · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20251 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Do LLMs Understand Dialogues? A Case Study on Dialogue Acts (2025 · 6 citations)
    On fine-grained dialogue act classification (MRDA meetings, 50 classes; Switchboard, 43) prompted LLMs do far worse than small fine-tuned models: LLaMA-3.1-70B few-shot reaches 19 macro-F1 / 31% accuracy on MRDA against 40 / 66% for a RoBERTa model with speaker-turn modelling, and GPT-4 with audio only 28 / 42%.
  2. Who is Speaking? Speaker-Aware Multiparty Dialogue Act Classification (2023 · 5 citations)
    The paper targets dialogue act (DA) classification in conversations with more than two participants. Earlier speaker-aware methods either assume a fixed, small set of speakers or reduce speaker information to a same/different flag, which effectively turns a meeting into a two-person exchange. The authors build on a…

 Co-authors here

2 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 9 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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