Kevin Lin

I am a PhD student at UC Berkeley working with Joey Gonzalez and Dan Klein where I am affiliated with Berkeley NLP, BAIR, and Sky Computing. I'm broadly interested in natural language processing and machine learning techniques that help people better interface with information. My research is supported by an NSF Graduate Research Fellowship. Previously, I was part of AI2's AllenNLP team.

Email  /  Google Scholar

profile photo
Research
RALF: Accuracy-Aware Scheduling for Feature Store Maintenance
Sarah Wooders, Xiangxi Mo, Amit Narang, Kevin Lin, Ion Stoica, Joe Hellerstein, Natacha Crooks, Joseph E. Gonzalez
VLDB 2024
code

MemGPT: Towards LLMs as Operating Systems
Charles Packer, Sarah Wooders, Kevin Lin, Vivian Fang, Shishir G. Patil Ion Stoica, Joseph E. Gonzalez
preprint
code

Few-Shot Adaptation for Parsing Contextual Utterances with LLMs
Kevin Lin, Patrick Xia, Hao Fang
AACL Findings 2023
code

Lost in the Middle: How Language Models Use Long Contexts
Nelson F. Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michel Bevilacqua, Fabio Petroni, Percy Liang
TACL 2023
code

Decomposing Complex Queries for Tip-of-the-tongue Retrieval
Kevin Lin, Kyle Lo, Joseph E. Gonzalez, Dan Klein
EMNLP Findings 2023

Constructing Taxonomies from Pretrained Language Models
Catherine Chen*, Kevin Lin*, Dan Klein (*equal contribution)
NAACL 2021
code

Evaluating Models' Local Decision Boundaries via Contrast Sets
Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, Ben Zhou
EMNLP Findings 2020
data

Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers
Zhuohan Li*, Eric Wallace*, Sheng Shen*, Kevin Lin*, Kurt Keutzer, Dan Klein, Joseph E. Gonzalez (*equal contribution)
ICML 2020

Neural Module Networks for Reasoning over Text
Nitish Gupta, Kevin Lin, Dan Roth, Sameer Singh, Matt Gardner
ICLR 2020
code

Quartz: An Open-Domain Dataset of Qualitative Relationship Questions
Oyvind Tafjord, Matt Gardner, Kevin Lin, Peter Clark
EMNLP, 2019  
data

Reasoning Over Paragraph Effects in Situations
Kevin Lin, Oyvind Tafjord, Peter Clark, Matt Gardner
MRQA@EMNLP, 2019  
leaderboard / project page

Grammar-based Neural Text-to-SQL Generation
Kevin Lin, Ben Bogin, Mark Neumann, Jonathan Berant, Matt Gardner
Arxiv, 2019  
code

Deepbase: Deep Inspection of Neural Networks
Thibault Sellam, Kevin Lin, Ian Yiran Huang, Michelle Yang, Carl Vondrick, Eugene Wu
SIGMOD, 2019  

“I Like the Way You Think!” Inspecting the Internal Logic of Recurrent Neural Networks
Thibault Sellam, Kevin Lin, Ian Yiran Huang, Carl Vondrick, Eugene Wu
SysML, 2018  


Thanks to Jon Barron for the website design!