Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Bhatia, Gagan"'
Recent advancements have significantly enhanced the capabilities of Multimodal Large Language Models (MLLMs) in generating and understanding image-to-text content. Despite these successes, progress is predominantly limited to English due to the scarc
Externí odkaz:
http://arxiv.org/abs/2407.18129
Arabic Optical Character Recognition (OCR) and Handwriting Recognition (HWR) pose unique challenges due to the cursive and context-sensitive nature of the Arabic script. This study introduces Qalam, a novel foundation model designed for Arabic OCR an
Externí odkaz:
http://arxiv.org/abs/2407.13559
Autor:
Alwajih, Fakhraddin, Nagoudi, El Moatez Billah, Bhatia, Gagan, Mohamed, Abdelrahman, Abdul-Mageed, Muhammad
Multimodal large language models (MLLMs) have proven effective in a wide range of tasks requiring complex reasoning and linguistic comprehension. However, due to a lack of high-quality multimodal resources in languages other than English, success of
Externí odkaz:
http://arxiv.org/abs/2403.01031
We introduce FinTral, a suite of state-of-the-art multimodal large language models (LLMs) built upon the Mistral-7b model and tailored for financial analysis. FinTral integrates textual, numerical, tabular, and image data. We enhance FinTral with dom
Externí odkaz:
http://arxiv.org/abs/2402.10986
Large language models (LLMs) finetuned to follow human instruction have recently exhibited significant capabilities in various English NLP tasks. However, their performance in grammatical error correction (GEC), especially on languages other than Eng
Externí odkaz:
http://arxiv.org/abs/2312.08400
Recently, large language models (LLMs) fine-tuned to follow human instruction have exhibited significant capabilities in various English NLP tasks. However, their performance in grammatical error correction (GEC) tasks, particularly in non-English la
Externí odkaz:
http://arxiv.org/abs/2308.04492
Autor:
Kwon, Sang Yun, Bhatia, Gagan, Nagoudi, El Moatez Billah, Inciarte, Alcides Alcoba, Abdul-Mageed, Muhammad
Intent detection and slot filling are critical tasks in spoken and natural language understanding for task-oriented dialog systems. In this work we describe our participation in the slot and intent detection for low-resource language varieties (SID4L
Externí odkaz:
http://arxiv.org/abs/2304.13292
We describe our contribution to the SemEVAl 2023 AfriSenti-SemEval shared task, where we tackle the task of sentiment analysis in 14 different African languages. We develop both monolingual and multilingual models under a full supervised setting (sub
Externí odkaz:
http://arxiv.org/abs/2304.11256
Autor:
Bhatia, Gagan J.1 gaganbhatia1981@gmail.com
Publikováno v:
International Management Review. 2023 Special issue, p13-20. 8p.
Autor:
Gupta, Charu, Shroff, Daraius, Gupta, Priyanka, Atri, Neelam, Bhatia, Gagan, Shroff, Cyrus M.
Publikováno v:
Retinal Cases & Brief Reports; Nov2022, Vol. 16 Issue 6, p793-798, 6p