Zobrazeno 1 - 10
of 3 479
pro vyhledávání: '"Murthy, V."'
Skyrmions, which are topologically stable magnetic structures, have manifested promising features to be used as an information carrier in new-age, non-volatile data storage devices. In this article, we show how the creation and stability of skyrmion
Externí odkaz:
http://arxiv.org/abs/2402.16060
Controlled creation of stable chiral spin textures is required to use them as an energy-efficient information carrier in spintronics. Here we have studied the stable creation of isolated chiral spin texture (skyrmion and antiskyrmion) and its pair th
Externí odkaz:
http://arxiv.org/abs/2310.12129
Designing a new clinical trial entails many decisions, such as defining a cohort and setting the study objectives to name a few, and therefore can benefit from recommendations based on exhaustive mining of past clinical trial records. Here, we propos
Externí odkaz:
http://arxiv.org/abs/2309.15979
Autor:
Mishra, Mayank, Kumar, Prince, Bhat, Riyaz, Murthy V, Rudra, Contractor, Danish, Tamilselvam, Srikanth
Prompting with natural language instructions has recently emerged as a popular method of harnessing the capabilities of large language models. Given the inherent ambiguity present in natural language, it is intuitive to consider the possible advantag
Externí odkaz:
http://arxiv.org/abs/2305.11790
We aim to investigate whether UNMT approaches with self-supervised pre-training are robust to word-order divergence between language pairs. We achieve this by comparing two models pre-trained with the same self-supervised pre-training objective. The
Externí odkaz:
http://arxiv.org/abs/2303.01191
Autor:
Murthy V, Rudra, Bhat, Riyaz, Gunasekara, Chulaka, Patel, Siva Sankalp, Wan, Hui, Dhamecha, Tejas Indulal, Contractor, Danish, Danilevsky, Marina
In this paper we explore the task of modeling semi-structured object sequences; in particular, we focus our attention on the problem of developing a structure-aware input representation for such sequences. Examples of such data include user activity
Externí odkaz:
http://arxiv.org/abs/2301.01015
Autor:
Mhaske, Arnav, Kedia, Harshit, Doddapaneni, Sumanth, Khapra, Mitesh M., Kumar, Pratyush, Murthy V, Rudra, Kunchukuttan, Anoop
We present, Naamapadam, the largest publicly available Named Entity Recognition (NER) dataset for the 11 major Indian languages from two language families. The dataset contains more than 400k sentences annotated with a total of at least 100k entities
Externí odkaz:
http://arxiv.org/abs/2212.10168
Autor:
Komala Lakshmi, Ch., Durga Rao, T., Bhavani, G., Sudhadhar, M., Sattibabu, B., Satya Narayana Murthy, V., Karthik, T., Asthana, Saket
Publikováno v:
In Journal of Solid State Chemistry December 2024 340
Autor:
Dhamecha, Tejas Indulal, Murthy V, Rudra, Bharadwaj, Samarth, Sankaranarayanan, Karthik, Bhattacharyya, Pushpak
We explore the impact of leveraging the relatedness of languages that belong to the same family in NLP models using multilingual fine-tuning. We hypothesize and validate that multilingual fine-tuning of pre-trained language models can yield better pe
Externí odkaz:
http://arxiv.org/abs/2109.10534