activity
20122023
most citedRecurrent Convolutional Strategies for Face Manipulation Detection in Videos

337 citations · 493 across the 15 of their papers we have counts for

collaborators
Showing cs.CLShow all

9 papers · 1 filter

cs.CL20223 cited

Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction

Kuan-Hao Huang, I-Hung Hsu, Premkumar Natarajan +2

We present a study on leveraging multilingual pre-trained generative language models for zero-shot cross-lingual event argument extraction (EAE). By formulating EAE as a language g…

cs.CL202112 cited

Societal Biases in Language Generation: Progress and Challenges

Emily Sheng, Kai-Wei Chang, Premkumar Natarajan +1

Technology for language generation has advanced rapidly, spurred by advancements in pre-training large models on massive amounts of data and the need for intelligent agents to comm…

cs.CL20212 cited

Personalized Entity Resolution with Dynamic Heterogeneous Knowledge Graph Representations

Ying Lin, Han Wang, Jiangning Chen +5

The growing popularity of Virtual Assistants poses new challenges for Entity Resolution, the task of linking mentions in text to their referent entities in a knowledge base. Specif…

cs.CL2020

"Nice Try, Kiddo": Investigating Ad Hominems in Dialogue Responses

Emily Sheng, Kai-Wei Chang, Premkumar Natarajan +1

Ad hominem attacks are those that target some feature of a person's character instead of the position the person is maintaining. These attacks are harmful because they propagate im…

cs.CL2020

Towards Controllable Biases in Language Generation

Emily Sheng, Kai-Wei Chang, Premkumar Natarajan +1

We present a general approach towards controllable societal biases in natural language generation (NLG). Building upon the idea of adversarial triggers, we develop a method to indu…

cs.CL201911 cited

The Woman Worked as a Babysitter: On Biases in Language Generation

Emily Sheng, Kai-Wei Chang, Premkumar Natarajan +1

We present a systematic study of biases in natural language generation (NLG) by analyzing text generated from prompts that contain mentions of different demographic groups. In this…