NeurIPS 2023 Workshop DistShift Submissions

An Empirical Study of Uncertainty Estimation Techniques for Detecting Drift in Data Streams
Anton Winter, Nicolas Jourdan, Tristan Wirth, Volker Knauthe, Arjan Kuijper
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone
Evolving Domain Adaptation of Pretrained Language Models for Text Classification
Yun-Shiuan Chuang, Rheeya Uppaal, Yi Wu, Luhang Sun, Makesh Narsimhan Sreedhar, Sijia Yang, Timothy T. Rogers, Junjie Hu
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone
Probing the Equivariance of Image Embeddings
Cyrus Rashtchian, Charles Herrmann, Chun-Sung Ferng, Ayan Chakrabarti, Dilip Krishnan, Deqing Sun, Da-Cheng Juan, Andrew Tomkins
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone
Can Transformer Models Generalize Via In-Context Learning Beyond Pretraining Data?
Steve Yadlowsky, Lyric Doshi, Nilesh Tripuraneni
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone
Iteratively Refined Behavior Regularization for Offline Reinforcement Learning
Xiaohan Hu, Yi Ma, Chenjun Xiao, YAN ZHENG, Jianye HAO
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone
AutoVP: An Automated Visual Prompting Framework and Benchmark
Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Sijia Liu, Tsung-Yi Ho
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Peng Cui
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone
Can Transformers In-Context Learn Task Mixtures?
Nilesh Tripuraneni, Lyric Doshi, Steve Yadlowsky
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone
OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection
Jingyang Zhang, Jingkang Yang, Pengyun Wang, Haoqi Wang, Yueqian Lin, Haoran Zhang, Yiyou Sun, Xuefeng Du, Yixuan Li, Ziwei Liu, Yiran Chen, Hai Li
- Published: 28 Oct 2023, Last Modified: 27 Sept 2024
- DistShift 2023 Oral
- Readers: Everyone
Ask Your Distribution Shift if Pre-Training is Right for You
Benjamin Cohen-Wang, Joshua Vendrow, Aleksander Madry
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone
One-Shot Domain Incremental Learning
NeurIPS 2023 Workshop DistShift Submission5 Authors
- 26 Sept 2023 (modified: 30 Mar 2024)
- NeurIPS 2023 Workshop DistShift Withdrawn Submission
- Readers: Everyone
SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore
Sewon Min, Suchin Gururangan, Eric Wallace, Weijia Shi, Hannaneh Hajishirzi, Noah A. Smith, Luke Zettlemoyer
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Oral
- Readers: Everyone
Bilevel Optimization to Learn Training Distributions for Language Modeling under Domain Shift
David Grangier, Pierre Ablin, Awni Hannun
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone
Tackling Concept Shift in Text Classification using Entailment-style modeling
Sumegh Roychowdhury, Siva Rajesh Kasa, Karan Gupta, Prasanna Srinivasa Murthy, Alok Chandra
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone
A Nearest Neighbor-Based Concept Drift Detection Strategy for Reliable Condition Monitoring
Nicolas Jourdan
- Published: 28 Oct 2023, Last Modified: 02 Apr 2024
- DistShift 2023 Poster
- Readers: Everyone