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Emre Can Acikgoz

Emre Can Acikgoz has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Dialogue systems; often with Dilek Hakkani-Tür, Gokhan Tur, Bingxiang He.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 3 · 30 works · 35 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 104 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9538

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

🎓University of Illinois Urbana-ChampaignUrbana · United States2024–2026 · 19 papersEmployment · Graduate Student, Computer Sciencecurrent🎓Koç UniversityIstanbul · Türkiye2022–2024 · 3 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 2Research subjects and languages the work is about.Dialogue systems · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Can a Single Model Master Both Multi-turn Conversations and Tool Use? CoALM: A Unified Conversational Agentic Language Model (2025 · 13 citations)
    Task-oriented dialogue (TOD) systems handle multi-turn conversations and track user goals well, but they are usually tied to a small fixed set of APIs.
  2. Current Agents Fail to Leverage World Model as Tool for Foresight (2026 · 1 citation)
    The paper asks whether today's vision-language agents can treat a generative world model as an optional external tool: a simulator they consult to preview the consequences of an action before committing to it in the real environment.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. ToolRL: Reward is All Tool Learning Needs ↗arXiv:2504.13958 · no summary yetCheng Qian et al.2025 · 94 citations
  2. Can a Single Model Master Both Multi-turn Conversations and Tool Use? CoALM: A Unified Conversational Agentic Language ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Emre Can Acikgoz, Jeremiah Greer, Akul Datta, et al.2025 · 13 citations
  3. Current Agents Fail to Leverage World Model as Tool for ForesightAnnual Meeting of the Association for Computational Linguistics (ACL)Cheng Qian, Emre Can Acikgoz, Bingxuan Li, et al.2026 · 1 citation

 Co-authors here

9 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 104 times (of the 149,439 papers whose bibliographies we read); 37 citing papers with a page here →.

Updated

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