Zobrazeno 1 - 10
of 458
pro vyhledávání: '"SHARMA, SHIVAM"'
Autor:
Acharya, Anurag, Sharma, Shivam, Cosbey, Robin, Subramanian, Megha, Howland, Scott, Glenski, Maria
A proliferation of Large Language Models (the GPT series, BLOOM, LLaMA, and more) are driving forward novel development of multipurpose AI for a variety of tasks, particularly natural language processing (NLP) tasks. These models demonstrate strong p
Externí odkaz:
http://arxiv.org/abs/2411.03542
Autor:
Phan, Hung, Acharya, Anurag, Meyur, Rounak, Chaturvedi, Sarthak, Sharma, Shivam, Parker, Mike, Nally, Dan, Jannesari, Ali, Pazdernik, Karl, Halappanavar, Mahantesh, Munikoti, Sai, Horawalavithana, Sameera
As LLMs become increasingly ubiquitous, researchers have tried various techniques to augment the knowledge provided to these models. Long context and retrieval-augmented generation (RAG) are two such methods that have recently gained popularity. In t
Externí odkaz:
http://arxiv.org/abs/2407.07321
Memes have evolved as a prevalent medium for diverse communication, ranging from humour to propaganda. With the rising popularity of image-focused content, there is a growing need to explore its potential harm from different aspects. Previous studies
Externí odkaz:
http://arxiv.org/abs/2405.11215
Autor:
Martin, Godwin, Sharma, Shivam K.
We initiate the study of an open EFT for finite-temperature holographic systems with interacting fermions. In particular, we do this for Yukawa interactions in the bulk using the real-time formalism (grSK geometry). From the bulk perspective, this st
Externí odkaz:
http://arxiv.org/abs/2403.10604
The ever-evolving social media discourse has witnessed an overwhelming use of memes to express opinions or dissent. Besides being misused for spreading malcontent, they are mined by corporations and political parties to glean the public's opinion. Th
Externí odkaz:
http://arxiv.org/abs/2403.10279
Autor:
Hee, Ming Shan, Sharma, Shivam, Cao, Rui, Nandi, Palash, Nakov, Preslav, Chakraborty, Tanmoy, Lee, Roy Ka-Wei
In the evolving landscape of online communication, moderating hate speech (HS) presents an intricate challenge, compounded by the multimodal nature of digital content. This comprehensive survey delves into the recent strides in HS moderation, spotlig
Externí odkaz:
http://arxiv.org/abs/2401.16727
Autor:
Sharma, Shivam
We obtain error approximation bounds between expected suprema of canonical processes that are generated by random vectors with independent coordinates and expected suprema of Gaussian processes. In particular, we obtain a sharper proximity estimate f
Externí odkaz:
http://arxiv.org/abs/2312.14308
Autor:
Augenstein, Isabelle, Baldwin, Timothy, Cha, Meeyoung, Chakraborty, Tanmoy, Ciampaglia, Giovanni Luca, Corney, David, DiResta, Renee, Ferrara, Emilio, Hale, Scott, Halevy, Alon, Hovy, Eduard, Ji, Heng, Menczer, Filippo, Miguez, Ruben, Nakov, Preslav, Scheufele, Dietram, Sharma, Shivam, Zagni, Giovanni
The emergence of tools based on Large Language Models (LLMs), such as OpenAI's ChatGPT, Microsoft's Bing Chat, and Google's Bard, has garnered immense public attention. These incredibly useful, natural-sounding tools mark significant advances in natu
Externí odkaz:
http://arxiv.org/abs/2310.05189
We introduce an innovative approach to automated sleep stage classification using EOG signals, addressing the discomfort and impracticality associated with EEG data acquisition. In addition, it is important to note that this approach is untapped in t
Externí odkaz:
http://arxiv.org/abs/2310.03757
Automated Sleep stage classification using raw single channel EEG is a critical tool for sleep quality assessment and disorder diagnosis. However, modelling the complexity and variability inherent in this signal is a challenging task, limiting their
Externí odkaz:
http://arxiv.org/abs/2309.07156