3 citations · 14 across the 20 of their papers we have counts for
8 papers · 1 filter
Learning to Persuade Exposes How Easily LLMs Abandon Correct Beliefs
Nimet Beyza Bozdag, Emre Can Acikgoz, Gokhan Tur +1
Persuasion is a core dynamic of natural language communication, shaping how large language models (LLMs) update beliefs, resolve disagreements, and reach decisions. As LLMs increas…
AcquisitionSynthesis: Targeted Data Generation using Acquisition Functions
Ishika Agarwal, Sofia Stoica, Emre Can Acikgoz +4
Data quality remains a critical bottleneck in developing capable, competitive models. Researchers have explored many ways to generate top quality samples. Some works rely on reject…
AURA: A Diagnostic Framework for Tracking User Satisfaction of Interactive Planning Agents
Takyoung Kim, Janvijay Singh, Shuhaib Mehri +6
The growing capabilities of large language models (LLMs) in instruction-following and context-understanding lead to the era of agents with numerous applications. Among these, task…
TD-EVAL: Revisiting Task-Oriented Dialogue Evaluation by Combining Turn-Level Precision with Dialogue-Level Comparisons
Emre Can Acikgoz, Carl Guo, Suvodip Dey +4
Task-oriented dialogue (TOD) systems are experiencing a revolution driven by Large Language Models (LLMs), yet the evaluation methodologies for these systems remain insufficient fo…
ReSpAct: Harmonizing Reasoning, Speaking, and Acting Towards Building Large Language Model-Based Conversational AI Agents
Vardhan Dongre, Xiaocheng Yang, Emre Can Acikgoz +3
Large language model (LLM)-based agents are increasingly employed to interact with external environments (e.g., games, APIs, world models) to solve user-provided tasks. However, cu…
Bridging the Bosphorus: Advancing Turkish Large Language Models through Strategies for Low-Resource Language Adaptation and Benchmarking
Emre Can Acikgoz, Mete Erdogan, Deniz Yuret
Large Language Models (LLMs) are becoming crucial across various fields, emphasizing the urgency for high-quality models in underrepresented languages. This study explores the uniq…
ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models
Ilker Kesen, Andrea Pedrotti, Mustafa Dogan +8
With the ever-increasing popularity of pretrained Video-Language Models (VidLMs), there is a pressing need to develop robust evaluation methodologies that delve deeper into their v…
Transformers on Multilingual Clause-Level Morphology
Emre Can Acikgoz, Tilek Chubakov, Müge Kural +2
This paper describes our winning systems in MRL: The 1st Shared Task on Multilingual Clause-level Morphology (EMNLP 2022 Workshop) designed by KUIS AI NLP team. We present our work…