Quasi-Dense Instance Similarity Learning. - Jiangmiao Pang; Linlu Qiu; Haofeng Chen; Qi Li; Trevor Darrell; Fisher Yu 001 (CoRR, 2020)

Quasi-Dense Similarity Learning for Multiple Object Tracking. - Jiangmiao Pang; Linlu Qiu; Xia Li 005; Haofeng Chen; Qi Li; Trevor Darrell; Fisher Yu 001 (CVPR, 2021)

Visually Grounded Concept Composition. - Bowen Zhang 002; Hexiang Hu; Linlu Qiu; Peter Shaw 004; Fei Sha (EMNLP (Findings), 2021)

Systematic Generalization on gSCAN: What is Nearly Solved and What is Next? - Linlu Qiu; Hexiang Hu; Bowen Zhang 002; Peter Shaw 004; Fei Sha (EMNLP (1), 2021)

Generate-and-Retrieve: Use Your Predictions to Improve Retrieval for Semantic Parsing. - Yury Zemlyanskiy; Michiel de Jong; Joshua Ainslie; Panupong Pasupat; Peter Shaw 004; Linlu Qiu; Sumit Sanghai; Fei Sha (COLING, 2022)

Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing. - Linlu Qiu; Peter Shaw 004; Panupong Pasupat; Tianze Shi; Jonathan Herzig; Emily Pitler; Fei Sha; Kristina Toutanova (EMNLP, 2022)

Improving Compositional Generalization with Latent Structure and Data Augmentation. - Linlu Qiu; Peter Shaw 004; Panupong Pasupat; Pawel Krzysztof Nowak; Tal Linzen; Fei Sha; Kristina Toutanova (NAACL-HLT, 2022)

QDTrack: Quasi-Dense Similarity Learning for Appearance-Only Multiple Object Tracking. - Tobias Fischer 004; Thomas E. Huang; Jiangmiao Pang; Linlu Qiu; Haofeng Chen; Trevor Darrell; Fisher Yu 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

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 R. Glass (EMNLP, 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 001; Nouha Dziri; Xiang Ren 001 (ICLR, 2024)

Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks. - Zhaofeng Wu; Linlu Qiu; Alexis Ross; Ekin Akyürek; Boyuan Chen 003; Bailin Wang; Najoung Kim; Jacob Andreas; Yoon Kim (NAACL-HLT, 2024)

Bias Amplification in Language Model Evolution: An Iterated Learning Perspective. - Yi Ren; Shangmin Guo; Linlu Qiu; Bailin Wang; Danica J. Sutherland (NeurIPS, 2024)

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 (CoRR, 2024)

The Surprising Effectiveness of Test-Time Training for Abstract Reasoning. - Ekin Akyürek; Mehul Damani; Linlu Qiu; Han Guo; Yoon Kim; Jacob Andreas (CoRR, 2024)

Bayesian Teaching Enables Probabilistic Reasoning in Large Language Models. - Linlu Qiu; Fei Sha; Kelsey R. Allen; Yoon Kim; Tal Linzen; Sjoerd van Steenkiste (CoRR, 2025)