4 citations · 8 across the 6 of their papers we have counts for
8 papers
FABLES: Evaluating faithfulness and content selection in book-length summarization
Yekyung Kim, Yapei Chang, Marzena Karpinska +5
While long-context large language models (LLMs) can technically summarize book-length documents (>100K tokens), the length and complexity of the documents have so far prohibited ev…
KNN-LM Does Not Improve Open-ended Text Generation
Shufan Wang, Yixiao Song, Andrew Drozdov +3
In this paper, we study the generation quality of interpolation-based retrieval-augmented language models (LMs). These methods, best exemplified by the KNN-LM, interpolate the LM's…
TABBIE: Pretrained Representations of Tabular Data
Hiroshi Iida, Dung Thai, Varun Manjunatha +1
Existing work on tabular representation learning jointly models tables and associated text using self-supervised objective functions derived from pretrained language models such as…
Explicit Bias Discovery in Visual Question Answering Models
Varun Manjunatha, Nirat Saini, Larry S. Davis
Researchers have observed that Visual Question Answering (VQA) models tend to answer questions by learning statistical biases in the data. For example, their answer to the question…
Learning to Color from Language
Varun Manjunatha, Mohit Iyyer, Jordan Boyd-Graber +1
Automatic colorization is the process of adding color to greyscale images. We condition this process on language, allowing end users to manipulate a colorized image by feeding in d…
Class Subset Selection for Transfer Learning using Submodularity
Varun Manjunatha, Srikumar Ramalingam, Tim K. Marks +1
In recent years, it is common practice to extract fully-connected layer (fc) features that were learned while performing image classification on a source dataset, such as ImageNet,…
The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives
Mohit Iyyer, Varun Manjunatha, Anupam Guha +4
Visual narrative is often a combination of explicit information and judicious omissions, relying on the viewer to supply missing details. In comics, most movements in time and spac…
SHOE: Supervised Hashing with Output Embeddings
Sravanthi Bondugula, Varun Manjunatha, Larry S. Davis +1
We present a supervised binary encoding scheme for image retrieval that learns projections by taking into account similarity between classes obtained from output embeddings. Our mo…