• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 51 matches

• 2023
• 
  Lisa Alazraki, Lluís Castrejón, Mostafa Dehghani, Fantine Huot, Jasper R. R. Uijlings, Thomas Mensink:
  How (not) to ensemble LVLMs for VQA. ICBINB 2023: 1-20
• 
  Joy Hsu, Gabriel Poesia, Jiajun Wu, Noah D. Goodman:
  Can Visual Scratchpads With Diagrammatic Abstractions Augment LLM Reasoning? ICBINB 2023: 21-28
• 
  Tomo Lazovich:
  Filter bubbles and affective polarization in user-personalized large language model outputs. ICBINB 2023: 29-37
• 
  Jay Mohta, Kenan E. Ak, Yan Xu, Mingwei Shen:
  Are large language models good annotators? ICBINB 2023: 38-48
• 
  Jie Ren, Yao Zhao, Tu Vu, Peter J. Liu, Balaji Lakshminarayanan:
  Self-Evaluation Improves Selective Generation in Large Language Models. ICBINB 2023: 49-64
• 
  Fady Rezk, Antreas Antoniou, Henry Gouk, Timothy M. Hospedales:
  Is Scaling Learned Optimizers Worth It? Evaluating The Value of VeLO's 4000 TPU Months. ICBINB 2023: 65-83
• 
  Adhithya Prakash Saravanan, Rafal Kocielnik, Roy Jiang, Pengrui Han, Anima Anandkumar:
  Exploring Social Bias in Downstream Applications of Text-to-Image Foundation Models. ICBINB 2023: 84-102
• 
  Leo Schwinn, David Dobre, Stephan Günnemann, Gauthier Gidel:
  Adversarial Attacks and Defenses in Large Language Models: Old and New Threats. ICBINB 2023: 103-117
• 
  Chenwei Wu, Li Erran Li, Stefano Ermon, Patrick Haffner, Rong Ge, Zaiwei Zhang:
  The Role of Linguistic Priors in Measuring Compositional Generalization of Vision-Language Models. ICBINB 2023: 118-126
• 
  Yuhui Zhang, Brandon McKinzie, Zhe Gan, Vaishaal Shankar, Alexander Toshev:
  Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation. ICBINB 2023: 127-133
• 
  Javier Antorán, Arno Blaas, Kelly Buchanan, Fan Feng, Vincent Fortuin, Sahra Ghalebikesabi, Andreas Kriegler, Ian Mason, David Rohde, Francisco J. R. Ruiz, Tobias Uelwer, Yubin Xie, Rui Yang:
  Proceedings on "I Can't Believe It's Not Better: Failure Modes in the Age of Foundation Models" at NeurIPS 2023 Workshops, 16 December 2023, New Orleans, Louisiana, USA. Proceedings of Machine Learning Research 239, PMLR 2023 [contents]
• 2022
• 
  Simran Kaur, Jeremy Cohen, Zachary Chase Lipton:
  On the Maximum Hessian Eigenvalue and Generalization. ICBINB 2022: 51-65
• 
  Tatiana Likhomanenko, Ronan Collobert, Navdeep Jaitly, Samy Bengio:
  Continuous Soft Pseudo-Labeling in ASR. ICBINB 2022: 66-84
• 
  Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham, Jesse C. Cresswell, Anthony L. Caterini:
  Denoising Deep Generative Models. ICBINB 2022: 41-50
• 
  Abhishek Moturu, Sayali Joshi, Andrea S. Doria, Anna Goldenberg:
  Volume-based Performance not Guaranteed by Promising Patch-based Results in Medical Imaging. ICBINB 2022: 85-93
• 
  Elre T. Oldewage, John Bronskill, Richard E. Turner:
  Adversarial Attacks are a Surprisingly Strong Baseline for Poisoning Few-Shot Meta-Learners. ICBINB 2022: 27-40
• 
  Rebecca Saul, Mohammad Mahmudul Alam, John Hurwitz, Edward Raff, Tim Oates, James Holt:
  Lempel-Ziv Networks. ICBINB 2022: 1-11
• 
  Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jörg Bornschein, Claudia Clopath, Yee Whye Teh, Razvan Pascanu:
  When Does Re-initialization Work? ICBINB 2022: 12-26
• 
  Javier Antorán, Arno Blaas, Fan Feng, Sahra Ghalebikesabi, Ian Mason, Melanie F. Pradier, David Rohde, Francisco J. R. Ruiz, Aaron Schein:
  Proceedings on "I Can't Believe It's Not Better! - Understanding Deep Learning Through Empirical Falsification" at NeurIPS 2022 Workshops, 03 December 2022, New Orleans, Louisiana, USA. Proceedings of Machine Learning Research 187, PMLR 2022 [contents]
• 2021
• 
  Dyah Adila, Dongyeop Kang:
  Understanding Out-of-distribution: A Perspective of Data Dynamics. ICBINB@NeurIPS 2021: 1-8
• 
  Arno Blaas, Xavier Suau, Jason Ramapuram, Nicholas Apostoloff, Luca Zappella:
  Challenges of Adversarial Image Augmentations. ICBINB@NeurIPS 2021: 9-14
• 
  Ali Borji:
  Shape Defense. ICBINB@NeurIPS 2021: 15-20
• 
  Anthony L. Caterini, Gabriel Loaiza-Ganem:
  Entropic Issues in Likelihood-Based OOD Detection. ICBINB@NeurIPS 2021: 21-26
• 
  Amélie Chatelain, Amine Djeghri, Daniel Hesslow, Julien Launay:
  Is the Number of Trainable Parameters All That Actually Matters? ICBINB@NeurIPS 2021: 27-32
• 
  Cian Eastwood, Ian Mason, Christopher K. I. Williams:
  Unit-level surprise in neural networks. ICBINB@NeurIPS 2021: 33-40
• 
  Soufiane Hayou, Arnaud Doucet, Judith Rousseau:
  The Curse of Depth in Kernel Regime. ICBINB@NeurIPS 2021: 41-47
• 
  Nitya Kasturi, Igor L. Markov:
  Text Ranking and Classification using Data Compression. ICBINB@NeurIPS 2021: 48-53
• 
  Rainer Kelz, Gerhard Widmer:
  Nonlinear Denoising, Linear Demixing. ICBINB@NeurIPS 2021: 54-58
• 
  Chelsea Murray, James Urquhart Allingham, Javier Antorán, José Miguel Hernández-Lobato:
  Addressing Bias in Active Learning with Depth Uncertainty Networks... or Not. ICBINB@NeurIPS 2021: 59-63
• 
  Mike Van Ness, Madeleine Udell:
  CDF Normalization for Controlling the Distribution of Hidden Nodes. ICBINB@NeurIPS 2021: 64-68

skipping 21 more matches