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20222024
most citedFETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation

14 citations · 37 across the 10 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CV2023★ 14 cited

FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation

Yuanxin Liu, Lei Li, Shuhuai Ren +5

Recently, open-domain text-to-video (T2V) generation models have made remarkable progress. However, the promising results are mainly shown by the qualitative cases of generated vid…

cs.CL2023★ 6 cited

RECALL: A Benchmark for LLMs Robustness against External Counterfactual Knowledge

Yi Liu, Lianzhe Huang, Shicheng Li +5

LLMs and AI chatbots have improved people's efficiency in various fields. However, the necessary knowledge for answering the question may be beyond the models' knowledge boundaries…

cs.CV2023

TESTA: Temporal-Spatial Token Aggregation for Long-form Video-Language Understanding

Shuhuai Ren, Sishuo Chen, Shicheng Li +2

Large-scale video-language pre-training has made remarkable strides in advancing video-language understanding tasks. However, the heavy computational burden of video encoding remai…

cs.CL2023

Communication Efficient Federated Learning for Multilingual Neural Machine Translation with Adapter

Yi Liu, Xiaohan Bi, Lei Li +3

Federated Multilingual Neural Machine Translation (Fed-MNMT) has emerged as a promising paradigm for institutions with limited language resources. This approach allows multiple ins…

cs.CL2023★ 3 cited

Fine-Tuning Deteriorates General Textual Out-of-Distribution Detection by Distorting Task-Agnostic Features

Sishuo Chen, Wenkai Yang, Xiaohan Bi +1

Detecting out-of-distribution (OOD) inputs is crucial for the safe deployment of natural language processing (NLP) models. Though existing methods, especially those based on the st…