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Aditi Chaudhary

7 accepted papers

2024

It’s All Relative! – A Synthetic Query Generation Approach for Improving Zero-Shot Relevance Prediction

NAACL 2024findings

Large language models (LLMs) have shown promising ability to generate synthetic query-document pairs by prompting with as few as 8 demonstrations. This has enabled building better IR models, especially for tasks with no training data. Typically, such synthetic query generation (QGen) approaches cond…

Cited by 8SourcePDFScholar
2024

WikiDO: A New Benchmark Evaluating Cross-Modal Retrieval for Vision-Language Models

NeurIPS 2024poster

Cross-modal (image-to-text and text-to-image) retrieval is an established task used in evaluation benchmarks to test the performance of vision-language models (VLMs). Several state-of-the-art VLMs (e.g. CLIP, BLIP-2) have achieved near-perfect performance on widely-used image-text retrieval benchmar…

Cited by 0SourceScholar
2023

Crossing the Threshold: Idiomatic Machine Translation through Retrieval Augmentation and Loss Weighting

EMNLP 2023long main

Idioms are common in everyday language, but often pose a challenge to translators because their meanings do not follow from the meanings of their parts. Despite significant advances, machine translation systems still struggle to translate idiomatic expressions. We provide a simple characterization o…

Cited by 0SourcecodeScholar
2023

Teacher Perception of Automatically Extracted Grammar Concepts for L2 Language Learning

EMNLP 2023long findings

One of the challenges in language teaching is how best to organize rules regarding syntax, semantics, or phonology in a meaningful manner. This not only requires content creators to have pedagogical skills, but also have that language's deep understanding. While comprehensive materials to develop…

Cited by 0SourceScholar
2021

Do Context-Aware Translation Models Pay the Right Attention?

ACL 2021long

Context-aware machine translation models are designed to leverage contextual information, but often fail to do so. As a result, they inaccurately disambiguate pronouns and polysemous words that require context for resolution. In this paper, we ask several questions: What contexts do human translator…

2021

Evaluating the Morphosyntactic Well-formedness of Generated Texts

EMNLP 2021main

Text generation systems are ubiquitous in natural language processing applications. However, evaluation of these systems remains a challenge, especially in multilingual settings. In this paper, we propose L’AMBRE – a metric to evaluate the morphosyntactic well-formedness of text using its dependency…

2021

When is Wall a Pared and when a Muro?: Extracting Rules Governing Lexical Selection

EMNLP 2021main

Learning fine-grained distinctions between vocabulary items is a key challenge in learning a new language. For example, the noun “wall” has different lexical manifestations in Spanish – “pared” refers to an indoor wall while “muro” refers to an outside wall. However, this variety of lexical distinct…

Cited by 3SourcePDFScholar