3 citations · 5 across the 17 of their papers we have counts for
6 papers · 1 filter
CAuSE: Decoding Multimodal Classifiers using Faithful Natural Language Explanation
Dibyanayan Bandyopadhyay, Soham Bhattacharjee, Mohammed Hasanuzzaman +1
Multimodal classifiers function as opaque black box models. While several techniques exist to interpret their predictions, very few of them are as intuitive and accessible as natur…
CorIL: Towards Enriching Indian Language to Indian Language Parallel Corpora and Machine Translation Systems
Soham Bhattacharjee, Mukund K Roy, Yathish Poojary +19
India's linguistic landscape is one of the most diverse in the world, comprising over 120 major languages and approximately 1,600 additional languages, with 22 officially recognize…
Beyond the Sentence: A Survey on Context-Aware Machine Translation with Large Language Models
Ramakrishna Appicharla, Baban Gain, Santanu Pal +1
Despite the popularity of the large language models (LLMs), their application to machine translation is relatively underexplored, especially in context-aware settings. This work pr…
Bridging the Linguistic Divide: A Survey on Leveraging Large Language Models for Machine Translation
Baban Gain, Dibyanayan Bandyopadhyay, Asif Ekbal +1
Large Language Models (LLMs) are rapidly reshaping machine translation (MT), particularly by introducing instruction-following, in-context learning, and preference-based alignment…
Thinking Machines: A Survey of LLM based Reasoning Strategies
Dibyanayan Bandyopadhyay, Soham Bhattacharjee, Asif Ekbal
Large Language Models (LLMs) are highly proficient in language-based tasks. Their language capabilities have positioned them at the forefront of the future AGI (Artificial General…
Balancing Global Quality and Pronoun-Specific Feedback for Context-Aware Machine Translation
Harshit Dhankhar, Baban Gain, Asif Ekbal +1
Context-aware machine translation can expose the evidence needed for pronoun choice, but standard fine-tuning does not explicitly prioritize these sparse discourse-sensitive decisi…