7.4k citations · 28.3k across the 205 of their papers we have counts for
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Linguistically Informed Evaluation of Multilingual ASR for African Languages
Fei-Yueh Chen, Lateef Adeleke, C. M. Downey
Word Error Rate (WER) mischaracterizes ASR models' performance for African languages by combining phonological, tone, and other linguistic errors into a single lexical error. By co…
DM-Codec: Distilling Multimodal Representations for Speech Tokenization
Md Mubtasim Ahasan, Md Fahim, Tasnim Mohiuddin +6
Recent advancements in speech-language models have yielded significant improvements in speech tokenization and synthesis. However, effectively mapping the complex, multidimensional…
Answering Ambiguous Questions with a Database of Questions, Answers, and Revisions
Haitian Sun, William W. Cohen, Ruslan Salakhutdinov
Many open-domain questions are under-specified and thus have multiple possible answers, each of which is correct under a different interpretation of the question. Answering such am…
Plan, Eliminate, and Track -- Language Models are Good Teachers for Embodied Agents
Yue Wu, So Yeon Min, Yonatan Bisk +5
Pre-trained large language models (LLMs) capture procedural knowledge about the world. Recent work has leveraged LLM's ability to generate abstract plans to simplify challenging co…
Generating Images with Multimodal Language Models
Jing Yu Koh, Daniel Fried, Ruslan Salakhutdinov
We propose a method to fuse frozen text-only large language models (LLMs) with pre-trained image encoder and decoder models, by mapping between their embedding spaces. Our model de…
Grounding Language Models to Images for Multimodal Inputs and Outputs
Jing Yu Koh, Ruslan Salakhutdinov, Daniel Fried
We propose an efficient method to ground pretrained text-only language models to the visual domain, enabling them to process arbitrarily interleaved image-and-text data, and genera…