Large Language Models

Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization
Comprehensive study powering the Google Cloud Vertex AI Prompt Optimizer (NeurIPS 2024).
Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Sercan Ö. Arık
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Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization
UQE: A Query Engine for Unstructured Databases
Neural Information Processing Systems (NeurIPS), 2024
Hanjun Dai, Bethany Yixin Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans
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UQE: A Query Engine for Unstructured Databases
Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments
EMNLP 2024
Han Zhou, Xingchen Wan, Yinhong Liu, Nigel Collier, Ivan Vulić, Anna Korhonen
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Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
Mitigating prompt biases and unifying existing calibration approaches without labeled data (ICLR 2024)
Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen, Katherine Heller, Subhrajit Roy
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Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
Working Memory Capacity of ChatGPT: An Empirical Study
AAAI Conference on Artificial Intelligence (AAAI), 2024
Dongyu Gong, Xingchen Wan, Dingmin Wang
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Working Memory Capacity of ChatGPT: An Empirical Study
AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning
Automatic discovery of families of high-performing PEFT configurations (TACL 2024)
Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen
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AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning
Universal Self-Adaptive Prompting
Empirical Methods in Natural Language Processing (EMNLP), 2023
Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Martin Eisenschlos, Sercan Ö. Arık, Tomas Pfister
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Universal Self-Adaptive Prompting
Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning
Orders-of-magnitude faster hard prompt search with SoTA performance (EMNLP Findings 2023)
Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen
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Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning
Better Zero-Shot Reasoning with Self-Adaptive Prompting
Findings of the Association for Computational Linguistics: ACL 2023
Xingchen Wan, Ruoxi Sun, Hanjun Dai, Sercan Ö. Arık, Tomas Pfister
PDF Cite Google Research Blog Abstract (Google Research) ACL Anthology Slides & Talk
Better Zero-Shot Reasoning with Self-Adaptive Prompting
Introducing Self-Adaptive Prompting for Large Language Models
Adaptive, black-box and automatic prompting methods to improve LLMs in zero-shot settings (ACL & EMNLP 2023)
Xingchen Wan
Last updated on 24 Oct 2023 8 min read
Google Research Blog COSP (ACL 2023) USP (EMNLP 2023)
Introducing Self-Adaptive Prompting for Large Language Models