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Large Language Models (LLMs) have shown impressive capabilities in various applications, but they still face various inconsistency issues. Existing works primarily focus on the inconsistency issues within a single LLM, while we…

Computation and Language · Computer Science 2024-11-15 Kai Xiong , Xiao Ding , Yixin Cao , Ting Liu , Bing Qin

Large language models (LLMs) have demonstrated great potential for domain-specific applications, such as the law domain. However, recent disputes over GPT-4's law evaluation raise questions concerning their performance in real-world legal…

Computation and Language · Computer Science 2023-10-19 Ruihao Shui , Yixin Cao , Xiang Wang , Tat-Seng Chua

Recent work has investigated the capabilities of large language models (LLMs) as zero-shot models for generating individual-level characteristics (e.g., to serve as risk models or augment survey datasets). However, when should a user have…

Large language models have demonstrated remarkable capabilities in natural language processing, yet their application to political discourse analysis remains underexplored. This paper introduces a novel approach to evaluating presidential…

Computation and Language · Computer Science 2024-09-13 Zhengliang Liu , Yiwei Li , Oleksandra Zolotarevych , Rongwei Yang , Tianming Liu

We evaluate the effectiveness of Large Language Models (LLMs) in assessing essay quality, focusing on their alignment with human grading. More precisely, we evaluate ChatGPT and Llama in the Automated Essay Scoring (AES) task, a crucial…

Computation and Language · Computer Science 2024-09-23 Anindita Kundu , Denilson Barbosa

As large language models (LLMs) take on greater roles in high-stakes decisions, alignment with human values is essential. Reliance on proprietary APIs limits reproducibility and broad participation. We study whether local open-source…

Artificial Intelligence · Computer Science 2025-11-18 Ephraiem Sarabamoun

Evaluating the quality of free-text explanations is a multifaceted, subjective, and labor-intensive task. Large language models (LLMs) present an appealing alternative due to their potential for consistency, scalability, and…

Computation and Language · Computer Science 2024-09-04 Ana Brassard , Benjamin Heinzerling , Keito Kudo , Keisuke Sakaguchi , Kentaro Inui

We evaluate recent Large Language Models (LLMs) on the challenging task of summarizing short stories, which can be lengthy, and include nuanced subtext or scrambled timelines. Importantly, we work directly with authors to ensure that the…

Computation and Language · Computer Science 2024-07-15 Melanie Subbiah , Sean Zhang , Lydia B. Chilton , Kathleen McKeown

Evaluating Large Language Models (LLMs) for mental health support is challenging due to the emotionally and cognitively complex nature of therapeutic dialogue. Existing benchmarks are limited in scale, reliability, often relying on…

Large Language Models (LLMs) such as OpenAI's GPT-4 and Meta's LLaMA offer a promising approach for scalable personality assessment from open-ended language. However, inferring personality traits remains challenging, and earlier work often…

Computation and Language · Computer Science 2025-07-22 Jianfeng Zhu , Ruoming Jin , Karin G. Coifman

The escalating global mental health crisis, marked by persistent treatment gaps, availability, and a shortage of qualified therapists, positions Large Language Models (LLMs) as a promising avenue for scalable support. While LLMs offer…

We evaluate two large language models (LLMs) ability to perform argumentative reasoning. We experiment with argument mining (AM) and argument pair extraction (APE), and evaluate the LLMs' ability to recognize arguments under progressively…

Computation and Language · Computer Science 2025-07-03 Adrian de Wynter , Tangming Yuan

Evaluating recommender systems remains a long-standing challenge, as offline methods based on historical user interactions and train-test splits often yield unstable and inconsistent results due to exposure bias, popularity bias, sampled…

We examined how model size, temperature, and prompt style affect Large Language Models' (LLMs) alignment within itself, between models, and with human in assessing clinical reasoning skills. Model size emerged as a key factor in LLM-human…

Computation and Language · Computer Science 2025-09-25 Julie Jung , Max Lu , Sina Chole Benker , Dogus Darici

This paper explores the potential of large language models (LLMs) as reliable analytical tools in linguistic research, focusing on the emergence of affective meanings in temporal expressions involving manner-of-motion verbs. While LLMs like…

Computation and Language · Computer Science 2025-07-15 Rosa Illan Castillo , Javier Valenzuela

We are exposed to much information trying to influence us, such as teaser messages, debates, politically framed news, and propaganda - all of which use persuasive language. With the recent interest in Large Language Models (LLMs), we study…

Computation and Language · Computer Science 2025-02-24 Amalie Brogaard Pauli , Isabelle Augenstein , Ira Assent

The rise of AI has fueled growing concerns about ``hype'' in machine learning papers, yet a reliable way to quantify rhetorical style independently of substantive content has remained elusive. Because bold language can stem from either…

Computation and Language · Computer Science 2025-12-24 Jingyi Qiu , Hong Chen , Zongyi Li

As the application of Large Language Models (LLMs) spreads across various industries, there are increasing concerns about the potential for their misuse, especially in sensitive areas such as political discourse. Deliberately aligning LLMs…

Computation and Language · Computer Science 2026-04-28 Lisa Korver , Mohamed Mostagir , Sherief Reda

We introduce Debate Speech Evaluation as a novel and challenging benchmark for assessing LLM judges. Evaluating debate speeches requires a deep understanding of the speech at multiple levels, including argument strength and relevance, the…

Computation and Language · Computer Science 2025-09-10 Noy Sternlicht , Ariel Gera , Roy Bar-Haim , Tom Hope , Noam Slonim

Recent work has explored the use of large language models (LLMs) to generate tutoring responses in mathematics, yet it remains unclear how closely their instructional behavior aligns with expert human practice. We analyze a dataset of math…

Computation and Language · Computer Science 2026-05-28 Ramatu Oiza Abdulsalam , Segun Aroyehun