Preserving Pre-trained Features Helps Calibrate Fine-tuned Language
Models

Preserving Pre-trained Features Helps Calibrate Fine-tuned Language Models

International Conference on Learning Representations (ICLR), 2023

30 May 2023

Jianfei Chen

Jun Zhu

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Papers citing "Preserving Pre-trained Features Helps Calibrate Fine-tuned Language Models"

13 / 13 papers shown

Title
From Calibration to Collaboration: LLM Uncertainty Quantification Should Be More Human-Centered Siddartha Devic Tejas Srinivasan Jesse Thomason Willie Neiswanger Willie Neiswanger 183 7 0 09 Jun 2025
Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review Toghrul Abbasli Kentaroh Toyoda Yuan Wang Leon Witt Muhammad Asif Ali Yukai Miao Dan Li Qingsong Wei UQCV 587 2 0 25 Apr 2025
Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRA Patryk Marszałek Klaudia Bałazy Jacek Tabor Tomasz Kuśmierczyk UQCV 152 1 0 17 Feb 2025
Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis Sanket Jantre Tianle Wang Gilchan Park Kriti Chopra Nicholas Jeon Xiaoning Qian Nathan M. Urban Byung-Jun Yoon 447 1 0 10 Feb 2025
DiTASK: Multi-Task Fine-Tuning with Diffeomorphic TransformationsComputer Vision and Pattern Recognition (CVPR), 2025 Krishna Sri Ipsit Mantri Carola-Bibiane Schönlieb Bruno Ribeiro Chaim Baskin Moshe Eliasof 419 5 0 09 Feb 2025
The Best Instruction-Tuning Data are Those That Fit Dylan Zhang Qirun Dai Hao Peng ALM 518 20 0 06 Feb 2025
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs Ruijia Niu D. Wu Rose Yu Yi-An Ma 468 2 0 09 Oct 2024
Correcting Negative Bias in Large Language Models through Negative Attention Score Alignment Sangwon Yu Jongyoon Song Bongkyu Hwang Hoyoung Kang Sooah Cho Junhwa Choi Seongho Joe Taehee Lee Youngjune Gwon Sungroh Yoon 538 9 0 31 Jul 2024
LoRA Dropout as a Sparsity Regularizer for Overfitting Control Yang Lin Xinyu Ma Xu Chu Yujie Jin Zhibang Yang Yasha Wang Hong-yan Mei 182 44 0 15 Apr 2024
Uncertainty quantification in fine-tuned LLMs using LoRA ensembles Oleksandr Balabanov Hampus Linander UQCV 459 26 0 19 Feb 2024
LoRA ensembles for large language model fine-tuning Xi Wang Laurence Aitchison Maja Rudolph UQCV 414 53 0 29 Sep 2023
CATfOOD: Counterfactual Augmented Training for Improving Out-of-Domain Performance and CalibrationConference of the European Chapter of the Association for Computational Linguistics (EACL), 2023 Rachneet Sachdeva Martin Tutek Iryna Gurevych OODD 240 16 0 14 Sep 2023
Bayesian Low-rank Adaptation for Large Language ModelsInternational Conference on Learning Representations (ICLR), 2023 Adam X. Yang Maxime Robeyns Xi Wang Laurence Aitchison AI4CE BDL 659 82 0 24 Aug 2023