Papers
Pretraining Data Detection for Large Language Models: A Divergence-based Calibration Method
Weichao Zhang, Ruqing Zhang, Jiafeng Guo et al.
Pretraining Language Models Using Translationese
Meet Doshi, Raj Dabre, Pushpak Bhattacharyya
PrExMe! Large Scale Prompt Exploration of Open Source LLMs for Machine Translation and Summarization Evaluation
Christoph Leiter, Steffen Eger
Principles for AI-Assisted Social Influence and Their Application to Social Mediation
Ian Perera, Alex Memory, Vera A. Kazakova et al.
PRISM: A New Lens for Improved Color Understanding
Arjun Reddy Akula, Garima Pruthi, Inderjit S Dhillon et al.
Privacy Evaluation Benchmarks for NLP Models
Wei Huang, Yinggui Wang, Cen Chen
Private Language Models via Truncated Laplacian Mechanism
Tianhao Huang, Tao Yang, Ivan Habernal et al.
Private prediction for large-scale synthetic text generation
Kareem Amin, Alex Bie, Weiwei Kong et al.
Probing Language Models on Their Knowledge Source
Zineddine Tighidet, Jiali Mei, Benjamin Piwowarski et al.
Probing the Capacity of Language Model Agents to Operationalize Disparate Experiential Context Despite Distraction
Sonny George, Chris Sypherd, Dylan Cashman
Probing the Depths of Language Models’ Contact-Center Knowledge for Quality Assurance
Digvijay Anil Ingle, Aashraya Sachdeva, Surya Prakash Sahu et al.
Problem-Oriented Segmentation and Retrieval: Case Study on Tutoring Conversations
Rose E Wang, Pawan Wirawarn, Kenny Lam et al.
ProConSuL: Project Context for Code Summarization with LLMs
Vadim Lomshakov, Andrey Podivilov, Sergey Savin et al.
PRoDeliberation: Parallel Robust Deliberation for End-to-End Spoken Language Understanding
Trang Le, Daniel Lazar, Suyoun Kim et al.
Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models
Seungone Kim, Juyoung Suk, Shayne Longpre et al.
Promoting Constructive Deliberation: Reframing for Receptiveness
Gauri Kambhatla, Matthew Lease, Ashwin Rajadesingan
Promoting Data and Model Privacy in Federated Learning through Quantized LoRA
Zhu JianHao, Changze Lv, Xiaohua Wang et al.
Prompt-Based Bias Calibration for Better Zero/Few-Shot Learning of Language Models
Kang He, Yinghan Long, Kaushik Roy
PromptIntern: Saving Inference Costs by Internalizing Recurrent Prompt during Large Language Model Fine-tuning
Jiaru Zou, Mengyu Zhou, Tao Li et al.
PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning
Gyeongman Kim, Doohyuk Jang, Eunho Yang
Prompt Leakage effect and mitigation strategies for multi-turn LLM Applications
Divyansh Agarwal, Alexander Fabbri, Ben Risher et al.
PRompt Optimization in Multi-Step Tasks (PROMST): Integrating Human Feedback and Heuristic-based Sampling
Yongchao Chen, Jacob Arkin, Yilun Hao et al.
PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval
Shengyao Zhuang, Xueguang Ma, Bevan Koopman et al.
Prompts have evil twins
Rimon Melamed, Lucas Hurley McCabe, Tanay Wakhare et al.
Prompt-Tuned Muti-Task Taxonomic Transformer (PTMTTaxoFormer)
Rajashekar Vasantha, Nhan Nguyen, Yue Zhang