Zobrazeno 1 - 10
of 5 739
pro vyhledávání: '"Niyogi, A."'
We have considered an effective field theory framework in which the Standard Model is extended by a non-renormalizable dimension six operator ($\frac{1}{\Lambda^2}(H^{\dagger}H)^3$) respecting the symmetries of the Standard Model. Such an operator ca
Externí odkaz:
http://arxiv.org/abs/2408.13326
In this paper, we have introduced a numerical method for solving the Friedmann equations of modified $f(\mathcal{G})$ gravity in the presence of pressureless matter, enabling us to predict the redshift behavior of the Hubble expansion rate. To evalua
Externí odkaz:
http://arxiv.org/abs/2408.03683
In this article, we study whether the slope functions of two functional regression models in two samples are associated with any arbitrary transformation (barring constant and linear transformation) or not along the vertical axis. In order to address
Externí odkaz:
http://arxiv.org/abs/2407.19502
Autor:
Niyogi, Mitodru, Bhattacharya, Arnab
In this paper, we present Paramanu-Ganita, a 208 million parameter novel Auto Regressive (AR) decoder based language model on mathematics. The model is pretrained from scratch at context size of 4096 on our curated mixed mathematical corpus. We evalu
Externí odkaz:
http://arxiv.org/abs/2404.14395
Autor:
Niyogi, Mitodru, Bhattacharya, Arnab
In this paper, we present PARAMANU-AYN, a language model based exclusively on case documents of the Supreme Court of India, the Constitution of India, and the Indian Penal Code. The novel Auto Regressive (AR) decoder based model is pretrained from sc
Externí odkaz:
http://arxiv.org/abs/2403.13681
Autor:
Niyogi, Pratim Guha, Zhong, Ping-Shou
We address the challenge of estimation in the context of constant linear effect models with dense functional responses. In this framework, the conditional expectation of the response curve is represented by a linear combination of functional covariat
Externí odkaz:
http://arxiv.org/abs/2402.13907
Autor:
Niyogi, Mitodru
Natural language (NL) to code suggestion systems assist developers in Integrated Development Environments (IDEs) by translating NL utterances into compilable code snippet. The current approaches mainly involve hard-coded, rule-based systems based on
Externí odkaz:
http://arxiv.org/abs/2402.06690
Autor:
Niyogi, Mitodru, Bhattacharya, Arnab
We present Gyan AI Paramanu ("atom"), a family of novel language models for Indian languages. It is a collection of auto-regressive monolingual, bilingual, and multilingual Indic language models pretrained from scratch on a single GPU for 10 Indian l
Externí odkaz:
http://arxiv.org/abs/2401.18034
Urban Building Energy Modeling (UBEM) is an emerging method to investigate urban design and energy systems against the increasing energy demand at urban and neighborhood levels. However, current UBEM methods are mostly physic-based and time-consuming
Externí odkaz:
http://arxiv.org/abs/2312.02375
This paper presents a Soft Labeling and Noisy Mixup-based open intent classification model (SNOiC). Most of the previous works have used threshold-based methods to identify open intents, which are prone to overfitting and may produce biased predictio
Externí odkaz:
http://arxiv.org/abs/2310.07306