Zobrazeno 1 - 10
of 110
pro vyhledávání: '"Strzalkowski, Tomek"'
Autor:
Bhaumik, Ankita, Strzalkowski, Tomek
Large language models (LLMs) have demonstrated impressive performance in mathematical and commonsense reasoning tasks using chain-of-thought (CoT) prompting techniques. But can they perform emotional reasoning by concatenating `Let's think step-by-st
Externí odkaz:
http://arxiv.org/abs/2408.04906
The identification of Figurative Language (FL) features in text is crucial for various Natural Language Processing (NLP) tasks, where understanding of the author's intended meaning and its nuances is key for successful communication. At the same time
Externí odkaz:
http://arxiv.org/abs/2406.08218
Publikováno v:
2024.lrec-main.1476
The behavior and decision making of groups or communities can be dramatically influenced by individuals pushing particular agendas, e.g., to promote or disparage a person or an activity, to call for action, etc.. In the examination of online influenc
Externí odkaz:
http://arxiv.org/abs/2405.00821
Social media platforms are popular tools for disseminating targeted information during major public events like elections or pandemics. Systematic analysis of the message traffic can provide valuable insights into prevailing opinions and social dynam
Externí odkaz:
http://arxiv.org/abs/2402.15571
Autor:
Pisano, Matthew, Ly, Peter, Sanders, Abraham, Yao, Bingsheng, Wang, Dakuo, Strzalkowski, Tomek, Si, Mei
Research into AI alignment has grown considerably since the recent introduction of increasingly capable Large Language Models (LLMs). Unfortunately, modern methods of alignment still fail to fully prevent harmful responses when models are deliberatel
Externí odkaz:
http://arxiv.org/abs/2312.00029
Autor:
Sanders, Abraham, Strzalkowski, Tomek, Si, Mei, Chang, Albert, Dey, Deepanshu, Braasch, Jonas, Wang, Dakuo
Recent advances in large-scale language modeling and generation have enabled the creation of dialogue agents that exhibit human-like responses in a wide range of conversational scenarios spanning a diverse set of tasks, from general chit-chat to focu
Externí odkaz:
http://arxiv.org/abs/2205.03692
Autor:
Santhanam, Sashank, Cheng, Zhuo, Mather, Brodie, Dorr, Bonnie, Bhatia, Archna, Hebenstreit, Bryanna, Zemel, Alan, Dalton, Adam, Strzalkowski, Tomek, Shaikh, Samira
Achieving true human-like ability to conduct a conversation remains an elusive goal for open-ended dialogue systems. We posit this is because extant approaches towards natural language generation (NLG) are typically construed as end-to-end architectu
Externí odkaz:
http://arxiv.org/abs/2009.12506
Autor:
Dalton, Adam, Aghaei, Ehsan, Al-Shaer, Ehab, Bhatia, Archna, Castillo, Esteban, Cheng, Zhuo, Dhaduvai, Sreekar, Duan, Qi, Islam, Md Mazharul, Karimi, Younes, Masoumzadeh, Amir, Mather, Brodie, Santhanam, Sashank, Shaikh, Samira, Strzalkowski, Tomek, Dorr, Bonnie J.
We describe Panacea, a system that supports natural language processing (NLP) components for active defenses against social engineering attacks. We deploy a pipeline of human language technology, including Ask and Framing Detection, Named Entity Reco
Externí odkaz:
http://arxiv.org/abs/2004.09662
Autor:
Bhatia, Archna, Dalton, Adam, Mather, Brodie, Santhanam, Sashank, Shaikh, Samira, Zemel, Alan, Strzalkowski, Tomek, Dorr, Bonnie J.
We present a paradigm for extensible lexicon development based on Lexical Conceptual Structure to support social engineering detection and response generation. We leverage the central notions of ask (elicitation of behaviors such as providing access
Externí odkaz:
http://arxiv.org/abs/2004.09050
Autor:
Dorr, Bonnie J., Bhatia, Archna, Dalton, Adam, Mather, Brodie, Hebenstreit, Bryanna, Santhanam, Sashank, Cheng, Zhuo, Shaikh, Samira, Zemel, Alan, Strzalkowski, Tomek
Social engineers attempt to manipulate users into undertaking actions such as downloading malware by clicking links or providing access to money or sensitive information. Natural language processing, computational sociolinguistics, and media-specific
Externí odkaz:
http://arxiv.org/abs/2002.10931