8 citations · 8 across the 7 of their papers we have counts for
7 papers
VC-Bench: Pioneering the Video Connecting Benchmark with a Dataset and Evaluation Metrics
Zhiyu Yin, Zhipeng Liu, Kehai Chen +5
While current video generation focuses on text or image conditions, practical applications like video editing and vlogging often need to seamlessly connect separate clips. In our w…
The Stochastic Parrot on LLM's Shoulder: A Summative Assessment of Physical Concept Understanding
Mo Yu, Lemao Liu, Junjie Wu +5
In a systematic way, we investigate a widely asked question: Do LLMs really understand what they say?, which relates to the more familiar term Stochastic Parrot. To this end, we pr…
TF-Attack: Transferable and Fast Adversarial Attacks on Large Language Models
Zelin Li, Kehai Chen, Lemao Liu +4
With the great advancements in large language models (LLMs), adversarial attacks against LLMs have recently attracted increasing attention. We found that pre-existing adversarial a…
Rethinking Targeted Adversarial Attacks For Neural Machine Translation
Junjie Wu, Lemao Liu, Wei Bi +1
Targeted adversarial attacks are widely used to evaluate the robustness of neural machine translation systems. Unfortunately, this paper first identifies a critical issue in the ex…
On the Hallucination in Simultaneous Machine Translation
Meizhi Zhong, Kehai Chen, Zhengshan Xue +3
It is widely known that hallucination is a critical issue in Simultaneous Machine Translation (SiMT) due to the absence of source-side information. While many efforts have been mad…
Context Consistency between Training and Testing in Simultaneous Machine Translation
Meizhi Zhong, Lemao Liu, Kehai Chen +2
Simultaneous Machine Translation (SiMT) aims to yield a real-time partial translation with a monotonically growing the source-side context. However, there is a counterintuitive phe…
Towards General Error Diagnosis via Behavioral Testing in Machine Translation
Junjie Wu, Lemao Liu, Dit-Yan Yeung
Behavioral testing offers a crucial means of diagnosing linguistic errors and assessing capabilities of NLP models. However, applying behavioral testing to machine translation (MT)…