21 citations · 66 across the 26 of their papers we have counts for
7 papers · 1 filter
Improving a Named Entity Recognizer Trained on Noisy Data with a Few Clean Instances
Zhendong Chu, Ruiyi Zhang, Tong Yu +4
To achieve state-of-the-art performance, one still needs to train NER models on large-scale, high-quality annotated data, an asset that is both costly and time-intensive to accumul…
AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models
Sicheng Zhu, Ruiyi Zhang, Bang An +6
Safety alignment of Large Language Models (LLMs) can be compromised with manual jailbreak attacks and (automatic) adversarial attacks. Recent studies suggest that defending against…
PDFTriage: Question Answering over Long, Structured Documents
Jon Saad-Falcon, Joe Barrow, Alexa Siu +4
Large Language Models (LLMs) have issues with document question answering (QA) in situations where the document is unable to fit in the small context length of an LLM. To overcome…
Summarization from Leaderboards to Practice: Choosing A Representation Backbone and Ensuring Robustness
David Demeter, Oshin Agarwal, Simon Ben Igeri +4
Academic literature does not give much guidance on how to build the best possible customer-facing summarization system from existing research components. Here we present analyses t…
Few-Shot Dialogue Summarization via Skeleton-Assisted Prompt Transfer in Prompt Tuning
Kaige Xie, Tong Yu, Haoliang Wang +6
In real-world scenarios, labeled samples for dialogue summarization are usually limited (i.e., few-shot) due to high annotation costs for high-quality dialogue summaries. To effici…
Learning the Visualness of Text Using Large Vision-Language Models
Gaurav Verma, Ryan A. Rossi, Christopher Tensmeyer +2
Visual text evokes an image in a person's mind, while non-visual text fails to do so. A method to automatically detect visualness in text will enable text-to-image retrieval and ge…
Summaries as Captions: Generating Figure Captions for Scientific Documents with Automated Text Summarization
Chieh-Yang Huang, Ting-Yao Hsu, Ryan Rossi +6
Good figure captions help paper readers understand complex scientific figures. Unfortunately, even published papers often have poorly written captions. Automatic caption generation…