Computational Linguistics Journal

Do LLMs have personalities?

This paper introduces LMLPA, a framework for assessing linguistic personalities of LLMs using adapted Big Five inventories + AI raters, validated for reliability and consistency.

📄 Read in Computational Linguistics: direct.mit.edu/coli/article...

Evaluating NLG remains challenging — even with LLMs.

This survey reviews LLM-based evaluation methods: prompting, fine-tuning, and human–LLM collaboration, and outlines key open problems.

📄 Read in Computational Linguistics: direct.mit.edu/coli/article...

LLMs can generate fluent text — but can they twist your tongue?

TwisterLister generates phoneme-aware tongue twisters, with a 17k-example dataset and phonologically constrained decoding.

📄 Read the paper in Computational Linguistics: direct.mit.edu/coli/article...

Can LLMs learn possible human languages but struggle with impossible ones?

Kallini et al. claimed evidence, but Hunter argues their key experiment conflates factors — the core question remains open.

📄 Read the article in Computational Linguistics: direct.mit.edu/coli/article...

Even state-of-the-art MT systems struggle with ambiguous words — especially rare senses.

DiBiMT is a new fully human-curated benchmark across 8 language pairs to study disambiguation bias in MT.

📄 Read the paper in Computational Linguistics: direct.mit.edu/coli/article...

We're honored to announce the recipient of the ACL 2025 Distinguished Service Award! 🏅 This award recognizes extraordinary and sustained contributions to the computational linguistics community.

📚The dissertation will be published in the CL journal.
💬Catch the talk right after the award presentation! #NLProc
Congratulations to all these outstanding dissertations in NLP and CL — the future of #NLProc is in excellent hands! 🙌

Sewon Min 🏆 presenting the essence of her thesis: Rethinking Data Use in Large Language Models -- It won the first ACL Computational Linguistics Doctoral Dissertation Award 🎓✨
#ACL2025NLP #CLJournal @complingjournal.bsky.social

📚Tom Sherborne: Modeling Cross-lingual Transfer for Semantic Parsing

Sherborne’s dissertation develops sophisticated methods for cross-lingual transfer into low-resource languages, demonstrating their effectiveness in the context of semantic parsing for integration with database APIs.

📚Ashish Sharma: Human-AI Collaboration to Support Mental Health and Well-Being

Sharma’s dissertation pushes the boundaries of human-AI collaboration along with research in empathy detection and generation, advancing the application of NLP to mental health

📚 Manling Li: Event-Centric Multimodal Knowledge Acquisition

Li’s dissertation offers a comprehensive framework for multimodal event extraction and reasoning, advancing important tasks such as video question answering and future event prediction

This year ACL inaugurates the ✨🎓ACL Computational Linguistics Doctoral Dissertation Award! 🎓✨
Instrumental for launching this inaugural prize is the Computational Linguistics Journal @CompLingJournal, with support of the ACL Exec.

#CLJournal #ComputationalLinguistics
#ACL2025NLP @CompLingJournal

🏆 Who will take home the very first award?

The inaugural ACL Computational Linguistics Doctoral Dissertation Award will be revealed Monday, July 28 (Day 1, 4pm) at #ACL2025.

Chaired by Kathy McKeown.

Any predictions? 🤔🔥

10. Socially Aware Language Technologies: Perspectives and Practices
(Last Words)
By: Diyi Yang, Dirk Hovy, David Jurgens, Barbara Plank

direct.mit.edu/coli/article...

9. LLM-based NLG Evaluation: Current Status and Challenges
(Survey)
By: Mingqi Gao, Xinyu Hu, Xunjian Yin, Jie Ruan, Xiao Pu, Xiaojun Wan

direct.mit.edu/coli/article...

8. Language Models and Externalism: A Reply to Mandelkern and Linzen
(Squib)
By: Gary Ostertag

direct.mit.edu/coli/article...

7. Kallini et al. (2024) Do Not Compare Impossible Languages with Constituency-based Ones
(Squib)
By: Tim Hunter

direct.mit.edu/coli/article...

6. LMLPA: Language Model Linguistic Personality Assessment
(Regular Article)
By: Jingyao Zheng, Xian Wang, Simo Hosio, Xiaoxian Xu, Lik-Hang Lee

direct.mit.edu/coli/article...

5. Dotless Arabic Text for Natural Language Processing
(Regular Article)
By: Maged S. Al-Shaibani, Irfan Ahmad

direct.mit.edu/coli/article...

4. Investigating Idiomaticity in Word Representations
(Regular Article)
By: Wei He, Tiago Kramer Vieira, Marcos Garcia, Carolina Scarton, Marco Idiart, Aline Villavicencio

direct.mit.edu/coli/article...

3. Eliciting and Improving the Causal Reasoning Abilities of Large Language Models with Conditional Statements
(Regular Article)
By: Xiao Liu, Da Yin, Chen Zhang, Dongyan Zhao, Yansong Feng

direct.mit.edu/coli/article...

2. Train and Constrain: Phonologically Informed Tongue Twister Generation from Topics and Paraphrases Open Access
(Regular Article)
By: Tyler Loakman, Chen Tang, Chenghua Lin

direct.mit.edu/coli/article...

1. DiBiMT: A Gold Evaluation Benchmark for Studying Lexical Ambiguity in Machine Translation
(Regular Article)
By: Federico Martelli, Stefano Perrella, Niccolò Campolungo, Tina Munda, Svetla Koeva, Carole Tiberius, Roberto Navigli

direct.mit.edu/coli/article...

Volume 51, Issue 2 📣 Access it at direct.mit.edu/coli/issue/5...

The articles included in this issue are listed in the comments below. 🧵

🚨 As LLMs generate more of the text we see daily, detecting AI-generated text is more critical than ever.

New survey from the University of Macau explores cutting-edge detection methods, key challenges, and future directions to ensure responsible AI use.

Read: direct.mit.edu/coli/article...

🔍 Neural semantic parsers are great – but often just parrot surface text.
Researchers from the University of Groningen propose a taxonomical parser that builds deeper, hierarchical meaning representations.

Read: direct.mit.edu/coli/article...

🚀 New from Queen Mary University of London: A unified framework for evaluating synthetic data generation from user-generated text! 📱💬

It tackles style, meaning, and privacy – paving the way for safe, shareable, high-quality synthetic language data.

Read: direct.mit.edu/coli/article...

How do humans understand novel sentence meanings? A new dataset (STS3k) from UniMelb & Hitotsubashi researchers tests compositionality in language models. Findings: hybrids of syntax + vectors better match human judgments than top transformers.🧠📚

Read: direct.mit.edu/coli/article...

Researchers from the University of Edinburgh, the University of Zurich, Supertext, and Microsoft introduce ACES, a challenging benchmark spanning 146 language pairs, in their 'Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets'.

Read: direct.mit.edu/coli/article...

Researchers from Georgetown University, LMU Munich, Abo Akademi, and Indiana University present “eRST: A Signaled Graph Theory of Discourse Relations and Organization”.

Read: direct.mit.edu/coli/article...