Xingchen Wan
Xingchen Wan
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Large Language Models
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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Google Research Blog
Abstract
OpenReview
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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Code
Abstract
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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Code
Abstract
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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Google Research Blog
Abstract (Google Research)
OpenReview
ACL Anthology
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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Code
Abstract
OpenReview
ACL Anthology
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
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Google Research Blog
Abstract (Google Research)
ACL Anthology
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)
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