activity
20212025
most citedReport from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challenges

24 citations · 34 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2025★ 1 cited

MiniMax-01: Scaling Foundation Models with Lightning Attention

MiniMax, Aonian Li, Bangwei Gong +87

We introduce MiniMax-01 series, including MiniMax-Text-01 and MiniMax-VL-01, which are comparable to top-tier models while offering superior capabilities in processing longer conte…

cs.CL2022★ 24 cited

Report from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challenges

Shikib Mehri, Jinho Choi, Luis Fernando D'Haro +13

This is a report on the NSF Future Directions Workshop on Automatic Evaluation of Dialog. The workshop explored the current state of the art along with its limitations and suggeste…

cs.CV2021★ 1 cited

Semi-Autoregressive Image Captioning

Xu Yan, Zhengcong Fei, Zekang Li +3

Current state-of-the-art approaches for image captioning typically adopt an autoregressive manner, i.e., generating descriptions word by word, which suffers from slow decoding issu…

cs.CL2021★ 7 cited

Towards Expressive Communication with Internet Memes: A New Multimodal Conversation Dataset and Benchmark

Zhengcong Fei, Zekang Li, Jinchao Zhang +2

As a kind of new expression elements, Internet memes are popular and extensively used in online chatting scenarios since they manage to make dialogues vivid, moving, and interestin…

cs.CL2021★ 1 cited

Addressing Inquiries about History: An Efficient and Practical Framework for Evaluating Open-domain Chatbot Consistency

Zekang Li, Jinchao Zhang, Zhengcong Fei +2

A good open-domain chatbot should avoid presenting contradictory responses about facts or opinions in a conversational session, known as its consistency capacity. However, evaluati…