Papers by Anuj Gupta

5 papers
Conversational Semantic Parsing (2020.emnlp-main)

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Challenge: Structured representations for task-oriented assistant systems are limited due to the limitations of the representation.
Approach: They propose a semantic representation for task-oriented conversational systems that can represent co-reference and context carryover.
Outcome: The proposed model improves the best results on ATIS, SNIPS, TOP and DSTC2 by up to 5 points for slot-carryover.
Semantic Span Annotation: An Exploratory Study of LLM Annotation (2026.acl-srw)

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Challenge: Structured span extraction research is siloed by context length, annotation task, and domain . Identifying a span within a natural language text and affixing it with a semantic label has been considered a core task in NLP .
Approach: They propose a framework for structured span annotation that integrates five datasets under a common JSONL format with character-level offsets.
Outcome: The proposed framework can generalize across four domains under three prompting configurations.
El Volumen Louder Por Favor: Code-switching in Task-oriented Semantic Parsing (2021.eacl-main)

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Challenge: Code-switching (CS) is the alternation of languages within an utterance or conversation.
Approach: They propose to use translation-and-align and augment with a generation model followed by match-and filter to improve CS generalizability of cross-lingual models when data for only one language is available.
Outcome: The proposed models improve when only English data is available alongside zero or a few CS training instances.
Semantic Parsing for Task Oriented Dialog using Hierarchical Representations (D18-1)

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Challenge: Existing work on task oriented dialog systems has limited expressive power to one intent per query and one slot label per token.
Approach: They propose a hierarchical annotation scheme for semantic parsing that allows representation of compositional queries.
Outcome: The proposed representation outperforms sequence-to-sequence approaches on a 44k annotated query dataset.
hinglishNorm - A Corpus of Hindi-English Code Mixed Sentences for Text Normalization (2020.coling-industry)

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Challenge: hinglishNorm is a human annotated corpus of Hindi-English code-mixed sentences for text normalization task.
Approach: They propose to annotate sentences in Hindi-English code-mixed sentences using a human annotated normalized form.
Outcome: The proposed corpus contains 13494 segments annotated for text normalization.

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