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Anandhavelu N

4 accepted papers

2025

ADAPTIVE IE: Investigating the Complementarity of Human-AI Collaboration to Adaptively Extract Information on-the-fly

COLING 2025main

Information extraction (IE) needs vary over time, where a flexible information extraction (IE) system can be useful. Despite this, existing IE systems are either fully supervised, requiring expensive human annotations, or fully unsupervised, extracting information that often do not cater to user’s n…

Cited by 1SourcePDFScholar
2022

Entity Extraction in Low Resource Domains with Selective Pre-training of Large Language Models

EMNLP 2022main

Transformer-based language models trained on large natural language corpora have been very useful in downstream entity extraction tasks. However, they often result in poor performances when applied to domains that are different from those they are pretrained on. Continued pretraining using unlabeled…

2021

ClauseRec: A Clause Recommendation Framework for AI-aided Contract Authoring

EMNLP 2021main

Contracts are a common type of legal document that frequent in several day-to-day business workflows. However, there has been very limited NLP research in processing such documents, and even lesser in generating them. These contracts are made up of clauses, and the unique nature of these clauses cal…

Cited by 10SourcePDFScholar
2021

Multi-Style Transfer with Discriminative Feedback on Disjoint Corpus

NAACL 2021long

Style transfer has been widely explored in natural language generation with non-parallel corpus by directly or indirectly extracting a notion of style from source and target domain corpus. A common shortcoming of existing approaches is the prerequisite of joint annotations across all the stylistic d…