56 citations · 121 across the 49 of their papers we have counts for
6 papers · 1 filter
FASA: Frequency-aware Sparse Attention
Yifei Wang, Yueqi Wang, Zhenrui Yue +6
The deployment of Large Language Models (LLMs) faces a critical bottleneck when handling lengthy inputs: the prohibitive memory footprint of the Key Value (KV) cache. To address th…
MOCHA: Are Code Language Models Robust Against Multi-Turn Malicious Coding Prompts?
Muntasir Wahed, Xiaona Zhou, Kiet A. Nguyen +5
Recent advancements in Large Language Models (LLMs) have significantly enhanced their code generation capabilities. However, their robustness against adversarial misuse, particular…
Rationalization for Explainable NLP: A Survey
Sai Gurrapu, Ajay Kulkarni, Lifu Huang +3
Recent advances in deep learning have improved the performance of many Natural Language Processing (NLP) tasks such as translation, question-answering, and text classification. How…
SAUCE: Truncated Sparse Document Signature Bit-Vectors for Fast Web-Scale Corpus Expansion
Muntasir Wahed, Daniel Gruhl, Alfredo Alba +5
Recent advances in text representation have shown that training on large amounts of text is crucial for natural language understanding. However, models trained without predefined n…
Drink Bleach or Do What Now? Covid-HeRA: A Study of Risk-Informed Health Decision Making in the Presence of COVID-19 Misinformation
Arkin Dharawat, Ismini Lourentzou, Alex Morales +1
Given the widespread dissemination of inaccurate medical advice related to the 2019 coronavirus pandemic (COVID-19), such as fake remedies, treatments and prevention suggestions, m…
Adapting Sequence to Sequence models for Text Normalization in Social Media
Ismini Lourentzou, Kabir Manghnani, ChengXiang Zhai
Social media offer an abundant source of valuable raw data, however informal writing can quickly become a bottleneck for many natural language processing (NLP) tasks. Off-the-shelf…