80 citations · 153 across the 16 of their papers we have counts for
6 papers · 1 filter
i-Code Studio: A Configurable and Composable Framework for Integrative AI
Yuwei Fang, Mahmoud Khademi, Chenguang Zhu +8
Artificial General Intelligence (AGI) requires comprehensive understanding and generation capabilities for a variety of tasks spanning different modalities and functionalities. Int…
LMGQS: A Large-scale Dataset for Query-focused Summarization
Ruochen Xu, Song Wang, Yang Liu +5
Query-focused summarization (QFS) aims to extract or generate a summary of an input document that directly answers or is relevant to a given query. The lack of large-scale datasets…
InheritSumm: A General, Versatile and Compact Summarizer by Distilling from GPT
Yichong Xu, Ruochen Xu, Dan Iter +4
While large models such as GPT-3 demonstrate exceptional performance in zeroshot and fewshot summarization tasks, their extensive serving and fine-tuning costs hinder their utiliza…
i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data
Ziyi Yang, Mahmoud Khademi, Yichong Xu +16
The convergence of text, visual, and audio data is a key step towards human-like artificial intelligence, however the current Vision-Language-Speech landscape is dominated by encod…
Sequence-level self-learning with multiple hypotheses
Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur +4
In this work, we develop new self-learning techniques with an attention-based sequence-to-sequence (seq2seq) model for automatic speech recognition (ASR). For untranscribed speech…
Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention
Yichong Xu, Chenguang Zhu, Shuohang Wang +7
Most of today's AI systems focus on using self-attention mechanisms and transformer architectures on large amounts of diverse data to achieve impressive performance gains. In this…