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V. Rudra Murthy
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2020 – today
- 2024
- [i12]Settaluri Lakshmi Sravanthi, Meet Doshi, Tankala Pavan Kalyan, V. Rudra Murthy, Pushpak Bhattacharyya, Raj Dabre:
PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities. CoRR abs/2401.07078 (2024) - [i11]Jay P. Gala, Thanmay Jayakumar, Jaavid Aktar Husain, Aswanth Kumar M., Mohammed Safi Ur Rahman Khan, Diptesh Kanojia, Ratish Puduppully, Mitesh M. Khapra, Raj Dabre, V. Rudra Murthy, Anoop Kunchukuttan:
Airavata: Introducing Hindi Instruction-tuned LLM. CoRR abs/2401.15006 (2024) - 2023
- [c16]Arnav Mhaske, Harshit Kedia, Sumanth Doddapaneni, Mitesh M. Khapra, Pratyush Kumar, V. Rudra Murthy, Anoop Kunchukuttan:
Naamapadam: A Large-Scale Named Entity Annotated Data for Indic Languages. ACL (1) 2023: 10441-10456 - [c15]Akash Rawat, Nazia Nafis, Dnyaneshwar Bhadane, Diptesh Kanojia, V. Rudra Murthy:
Modelling Political Aggression on Social Media Platforms. WASSA@ACL 2023: 497-510 - [i10]Tamali Banerjee, V. Rudra Murthy, Pushpak Bhattacharyya:
Denoising-based UNMT is more robust to word-order divergence than MASS-based UNMT. CoRR abs/2303.01191 (2023) - 2022
- [c14]V. Rudra Murthy, Pallab Bhattacharjee, Rahul Sharnagat, Jyotsana Khatri, Diptesh Kanojia, Pushpak Bhattacharyya:
HiNER: A large Hindi Named Entity Recognition Dataset. LREC 2022: 4467-4476 - [i9]V. Rudra Murthy, Pallab Bhattacharjee, Rahul Sharnagat, Jyotsana Khatri, Diptesh Kanojia, Pushpak Bhattacharyya:
HiNER: A Large Hindi Named Entity Recognition Dataset. CoRR abs/2204.13743 (2022) - [i8]Arnav Mhaske, Harshit Kedia, Sumanth Doddapaneni, Mitesh M. Khapra, Pratyush Kumar, V. Rudra Murthy, Anoop Kunchukuttan:
Naamapadam: A Large-Scale Named Entity Annotated Data for Indic Languages. CoRR abs/2212.10168 (2022) - 2021
- [j2]Jyotsana Khatri
, V. Rudra Murthy, Tamali Banerjee, Pushpak Bhattacharyya:
Simple measures of bridging lexical divergence help unsupervised neural machine translation for low-resource languages. Mach. Transl. 35(4): 711-744 (2021) - [c13]Tejas I. Dhamecha, V. Rudra Murthy, Samarth Bharadwaj, Karthik Sankaranarayanan, Pushpak Bhattacharyya:
Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages. EMNLP (1) 2021: 8584-8595 - [c12]Tamali Banerjee, V. Rudra Murthy, Pushpak Bhattacharya:
Crosslingual Embeddings are Essential in UNMT for distant languages: An English to IndoAryan Case Study. MTSummit (1) 2021: 23-34 - [c11]Tamali Banerjee, V. Rudra Murthy, Pushpak Bhattacharya:
Scrambled Translation Problem: A Problem of Denoising UNMT. MTSummit (1) 2021: 127-138 - [c10]Jyotsana Khatri, V. Rudra Murthy, Pushpak Bhattacharyya:
Language Model Pretraining and Transfer Learning for Very Low Resource Languages. WMT@EMNLP 2021: 995-998 - [i7]Sandeep Mathias, V. Rudra Murthy, Diptesh Kanojia, Pushpak Bhattacharyya:
Cognitively Aided Zero-Shot Automatic Essay Grading. CoRR abs/2102.11258 (2021) - [i6]Tamali Banerjee, V. Rudra Murthy, Pushpak Bhattacharyya:
Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study. CoRR abs/2106.04995 (2021) - [i5]Tejas Indulal Dhamecha, V. Rudra Murthy, Samarth Bharadwaj, Karthik Sankaranarayanan, Pushpak Bhattacharyya:
Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages. CoRR abs/2109.10534 (2021) - 2020
- [c9]Jyotsana Khatri, V. Rudra Murthy, Pushpak Bhattacharyya:
A Study of Efficacy of Cross-lingual Word Embeddings for Indian Languages. COMAD/CODS 2020: 347-348 - [c8]Girishkumar Ponkiya, V. Rudra Murthy, Pushpak Bhattacharyya, Girish Keshav Palshikar:
Looking inside Noun Compounds: Unsupervised Prepositional and Free Paraphrasing using Language Models. EMNLP (Findings) 2020: 4313-4323 - [c7]Sandeep Mathias, V. Rudra Murthy, Diptesh Kanojia, Pushpak Bhattacharyya:
Cognitively Aided Zero-Shot Automatic Essay Grading. ICON 2020: 175-180 - [c6]Sandeep Mathias, V. Rudra Murthy, Diptesh Kanojia, Abhijit Mishra, Pushpak Bhattacharyya:
Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour. AACL/IJCNLP 2020: 858-872 - [i4]Sandeep Mathias
, V. Rudra Murthy, Diptesh Kanojia, Abhijit Mishra, Pushpak Bhattacharyya:
Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour. CoRR abs/2005.12078 (2020)
2010 – 2019
- 2019
- [j1]V. Rudra Murthy
, Mitesh M. Khapra, Pushpak Bhattacharyya:
Improving NER Tagging Performance in Low-Resource Languages via Multilingual Learning. ACM Trans. Asian Low Resour. Lang. Inf. Process. 18(2): 9:1-9:20 (2019) - [c5]V. Rudra Murthy
, Anoop Kunchukuttan, Pushpak Bhattacharyya:
Addressing word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages. NAACL-HLT (1) 2019: 3868-3873 - [i3]Tamali Banerjee, V. Rudra Murthy, Pushpak Bhattacharyya:
Ordering Matters: Word Ordering Aware Unsupervised NMT. CoRR abs/1911.01212 (2019) - 2018
- [c4]V. Rudra Murthy
, Anoop Kunchukuttan, Pushpak Bhattacharyya:
Judicious Selection of Training Data in Assisting Language for Multilingual Neural NER. ACL (2) 2018: 401-406 - [i2]V. Rudra Murthy, Anoop Kunchukuttan, Pushpak Bhattacharyya:
Addressing word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages. CoRR abs/1811.00383 (2018) - 2016
- [c3]V. Rudra Murthy
, Pushpak Bhattacharyya:
A Deep Learning Solution to Named Entity Recognition. CICLing (1) 2016: 427-438 - [i1]Rudramurthy V, Mitesh M. Khapra, Pushpak Bhattacharyya:
Sharing Network Parameters for Crosslingual Named Entity Recognition. CoRR abs/1607.00198 (2016) - 2015
- [c2]Sudha Bhingardive, Dhirendra Singh, Rudramurthy V, Pushpak Bhattacharyya:
Using Word Embeddings for Bilingual Unsupervised WSD. ICON 2015: 59-64 - [c1]Sudha Bhingardive, Dhirendra Singh, Rudramurthy V, Hanumant Harichandra Redkar, Pushpak Bhattacharyya:
Unsupervised Most Frequent Sense Detection using Word Embeddings. HLT-NAACL 2015: 1238-1243
Coauthor Index
aka: Pushpak Bhattacharya
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last updated on 2024-08-02 20:18 CEST by the dblp team
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