Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 5: Tutorial Abstracts)
Inverse Reinforcement Learning Meets Large Language Model Alignment (2025.acl-tutorials)
Copied to clipboard
| Challenge: | This tutorial will provide a comprehensive review of recent advances in LLM alignment . it will highlight the necessity of constructing neural reward models from human data . |
| Approach: | This tutorial will provide a comprehensive review of recent advances in LLM alignment through the lens of inverse reinforcement learning. |
| Outcome: | This tutorial will provide a comprehensive review of recent advances in LLM alignment through the lens of inverse reinforcement learning (IRL). |
Eye Tracking and NLP (2025.acl-tutorials)
Copied to clipboard
| Challenge: | tutorial combines eye tracking during reading with NLP . outlines how eye movements in reading can be leveraged for NLP methods . |
| Approach: | The tutorial combines eye tracking during reading with NLP . it covers eye movements in reading, integrating eye movement data in NLP models . |
| Outcome: | The tutorial outlines how eye movements in reading can be leveraged for NLP . it provides the essential background for conducting research on joint modeling of eye movements and text. |
Uncertainty Quantification for Large Language Models (2025.acl-tutorials)
Copied to clipboard
| Challenge: | Large language models (LLMs) produce hallucinations, which undermine user trust and reliability. |
| Approach: | This tutorial offers the first systematic introduction to uncertainty quantification (UQ) for LLMs in text generation tasks. |
| Outcome: | The proposed framework provides tools for communicating the reliability of a model answer. |
Human-AI Collaboration: How AIs Augment Human Teammates (2025.acl-tutorials)
Copied to clipboard
| Challenge: | Despite the potential of general-purpose models, they are far from perfect, excelling at certain tasks while struggling with others. |
| Approach: | This tutorial will review recent developments related to human-AI teaming and collaboration. |
| Outcome: | This tutorial will review recent developments related to human-AI teaming and collaboration. |
Navigating Ethical Challenges in NLP: Hands-on strategies for students and researchers (2025.acl-tutorials)
Copied to clipboard
Luciana Benotti, Fanny Ducel, Karën Fort, Guido Ivetta, Zhijing Jin, Min-Yen Kan, Seunghun J. Lee, Minzhi Li, Margot Mieskes, Adriana Pagano
| Challenge: | This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues . participants will gain practical experience on when to flag a paper for ethics review . |
| Approach: | This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues . participants will gain practical experience on when to flag a paper for ethics review . |
| Outcome: | This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues . participants will gain practical experience on when to flag a paper for ethics review . |
NLP for Counterspeech against Hate and Misinformation (CSHAM) (2025.acl-tutorials)
Copied to clipboard
| Challenge: | tutorial aims to show how counterspeech is used to tackle abuse and misinformation by individuals, activists and organisations. |
| Approach: | tutorial aims to show how counterspeech is currently used to tackle abuse and misinformation . will also show how Natural Language Processing (NLP) and Generation (NLG) can be applied to automate its production. |
| Outcome: | The tutorial will bring diverse multidisciplinary perspectives to safety research . case studies from industry and public policy will be included . |
Synthetic Data in the Era of Large Language Models (2025.acl-tutorials)
Copied to clipboard
| Challenge: | 'synthetic data' is a data generated with the assistance of large language models to make dataset construction faster and cheaper. |
| Approach: | This tutorial seeks to build a shared understanding of recent progress in synthetic data generation from NLP and related fields by grouping and describing major methods, applications, and open problems. |
| Outcome: | This tutorial will describe methods, applications, and open problems that have been developed and are being used to improve the quality and efficiency of synthetic data generation. |
Guardrails and Security for LLMs: Safe, Secure and Controllable Steering of LLM Applications (2025.acl-tutorials)
Copied to clipboard
Traian Rebedea, Leon Derczynski, Shaona Ghosh, Makesh Narsimhan Sreedhar, Faeze Brahman, Liwei Jiang, Bo Li, Yulia Tsvetkov, Christopher Parisien, Yejin Choi
| Challenge: | Pretrained generative models provide novel ways for users to interact with computers. |
| Approach: | This tutorial provides an overview of key guardrail mechanisms developed for LLMs along with evaluation methodologies and a detailed security assessment protocol. |
| Outcome: | This tutorial provides an overview of key guardrail mechanisms developed for LLMs, along with evaluation methodologies and a detailed security assessment protocol. |