I’m a PhD student at MIT EECS and CSAIL, advised by Yoon Kim. I’m interested in natural language processing. Previously, I was an AI Resident at Google Research, where I worked with Fei Sha and Peter Shaw. I received my Master’s degree from Georgia Tech and Bachelor’s degree from the University of Hong Kong.
Publications
Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps
Yung-Sung Chuang, Linlu Qiu, Cheng-Yu Hsieh, Ranjay Krishna, Yoon Kim, James Glass
EMNLP 2024
[code]
Learning to Reason via Program Generation, Emulation, and Search
Nathaniel Weir*, Muhammad Khalifa*, Linlu Qiu, Orion Weller, Peter Clark
NeurIPS 2024
Language Model Evolution: An Iterated Learning Perspective
Yi Ren, Shangmin Guo, Linlu Qiu, Bailin Wang, Danica J. Sutherland
NeurIPS 2024
Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement
Linlu Qiu, Liwei Jiang, Ximing Lu, Melanie Sclar, Valentina Pyatkin, Chandra Bhagavatula, Bailin Wang, Yoon Kim, Yejin Choi, Nouha Dziri, Xiang Ren
ICLR 2024 (Oral)
[code]
Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks
Zhaofeng Wu, Linlu Qiu, Alexis Ross, Ekin Akyürek, Boyuan Chen, Bailin Wang, Najoung Kim, Jacob Andreas, Yoon Kim
NAACL 2024
[code]
QDTrack: Quasi-Dense Similarity Learning for Appearance-Only Multiple Object Tracking
Tobias Fischer, Thomas E. Huang, Jiangmiao Pang, Linlu Qiu, Haofeng Chen, Trevor Darrell, Fisher Yu
TPAMI 2023
Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing
Linlu Qiu, Peter Shaw, Panupong Pasupat, Tianze Shi, Jonathan Herzig, Emily Pitler, Fei Sha, Kristina Toutanova
EMNLP 2022
[data]
Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing
Yury Zemlyanskiy, Michiel de Jong, Joshua Ainslie, Panupong Pasupat, Peter Shaw, Linlu Qiu, Sumit Sanghai, Fei Sha
COLING 2022
Improving Compositional Generalization with Latent Structure and Data Augmentation
Linlu Qiu*, Peter Shaw*, Panupong Pasupat, Paweł Krzysztof Nowak, Tal Linzen, Fei Sha, Kristina Toutanova
NAACL 2022
[code]
Systematic Generalization on gSCAN: What is Nearly Solved and What is Next?
Linlu Qiu, Hexiang Hu, Bowen Zhang, Peter Shaw, and Fei Sha
EMNLP 2021
[code]
Visually Grounded Concept Composition
Bowen Zhang, Hexiang Hu, Linlu Qiu, Peter Shaw, and Fei Sha
Findings of EMNLP 2021
Quasi-Dense Similarity Learning for Multiple Object Tracking
Jiangmiao Pang, Linlu Qiu, Xia Li, Haofeng Chen, Qi Li, Trevor Darrell, and Fisher Yu
CVPR 2021
[code]
Experience
Student Researcher, Google Research, June 2024 -
Mentors: Sjoerd van Steenkiste, Tal Linzen
Research Intern, Allen Institute for AI, May 2023 - August 2023
Mentors: Nouha Dziri, Xiang Ren