Papers
Positive Experience Reflection for Agents in Interactive Text Environments
Philip Lippmann, Matthijs T. J. Spaan, Jie Yang
Powerformer: Efficient and High-Accuracy Privacy-Preserving Language Model with Homomorphic Encryption
Dongjin Park, Eunsang Lee, Joon-Woo Lee
Power(ful) Associations: Rethinking “Stereotype” for NLP
Hannah Devinney
PQR: Improving Dense Retrieval via Potential Query Modeling
Junfeng Kang, Rui Li, Qi Liu et al.
Practical Solutions to Practical Problems in Developing Argument Mining Systems
Debela Gemechu, Ramon Ruiz-Dolz, John Lawrence et al.
Praetor: A Fine-Grained Generative LLM Evaluator with Instance-Level Customizable Evaluation Criteria
Yongqi Leng, Renren Jin, Yue Chen et al.
Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges
Bolei Ma, Yuting Li, Wei Zhou et al.
PRAISE: Enhancing Product Descriptions with LLM-Driven Structured Insights
Adnan Qidwai, Srija Mukhopadhyay, Prerana Khatiwada et al.
Pre3: Enabling Deterministic Pushdown Automata for Faster Structured LLM Generation
Junyi Chen, Shihao Bai, Zaijun Wang et al.
P-React: Synthesizing Topic-Adaptive Reactions of Personality Traits via Mixture of Specialized LoRA Experts
Yuhao Dan, Jie Zhou, Qin Chen et al.
Pre-annotation Matters: A Comparative Study on POS and Dependency Annotation for an Alsatian Dialect
Delphine Bernhard, Nathanaël Beiner, Barbara Hoff
Precision vs. Perturbation: Robustness Analysis of Synonym Attacks in Ukrainian NLP
Volodymyr Mudryi, Oleksii Ignatenko
PreClinIE: An Annotated Corpus for Information Extraction in Preclinical Studies
Simona Doneva, Hanna Hubarava, Pia Härvelid et al.
Predicate-Conditional Conformalized Answer Sets for Knowledge Graph Embeddings
Yuqicheng Zhu, Daniel Hernández, Yuan He et al.
PredictaBoard: Benchmarking LLM Score Predictability
Lorenzo Pacchiardi, Konstantinos Voudouris, Ben Slater et al.
Predicting Depression in Screening Interviews from Interactive Multi-Theme Collaboration
Xianbing Zhao, Yiqing Lyu, Di Wang et al.
Predicting Emotion Intensity in Text Using Transformer-Based Models
Temitope Oladepo, Oluwatobi Abiola, Tolulope Abiola et al.
Predicting Implicit Arguments in Procedural Video Instructions
Anil Batra, Laura Sevilla-Lara, Marcus Rohrbach et al.
Predicting The Scholarly Impact of Research Papers Using Retrieval-Augmented LLMs
Tamjid Azad, Ibrahim Al Azher, Sagnik Ray Choudhury et al.
Predicting Through Generation: Why Generation Is Better for Prediction
Md Kowsher, Nusrat Jahan Prottasha, Prakash Bhat et al.
Predicting Turn-Taking and Backchannel in Human-Machine Conversations Using Linguistic, Acoustic, and Visual Signals
Yuxin Lin, Yinglin Zheng, Ming Zeng et al.
Prediction-Augmented Generation for Automatic Diagnosis Tasks
Chan-Yang Ju, Dong-Ho Lee
Prediction Hubs are Context-Informed Frequent Tokens in LLMs
Beatrix Miranda Ginn Nielsen, Iuri Macocco, Marco Baroni