Papers with QUEST
QUEST: Efficient Extreme Multi-Label Text Classification with Large Language Models on Commodity Hardware (2024.findings-emnlp)
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| Challenge: | Extreme multi-label text classification (EMTC) involves predicting multiple labels from a vast pool of candidates based on a user’s textual query. |
| Approach: | They propose a Quantized and Efficient Learning with Sampling Technique that uses a hash sampling module to reduce the data volume to one-fourth of its original size. |
| Outcome: | Extensive experiments show that QUEST outperforms existing methods while requiring fewer computational resources. |
RefCo and its Checker: Improving Language Documentation Corpora’s Reusability Through a Semi-Automatic Review Process (2022.lrec-1)
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| Challenge: | QUEST aims to ensure the reusability of audio-visual datasets . documenting endangered and minority languages is one of the current goals of linguistic research . |
| Approach: | They propose to establish a semi-automatic review process for existing and work-in-progress corpora based on these criteria . goal is to increase the quality of a corpus by increasing its reusability. |
| Outcome: | The project aims to improve the quality of language documentation by increasing its reusability. |
QUEST: A Natural Language Interface to Relational Databases (L18-1)
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| Challenge: | Current systems focus on simple queries but neglect nested queries . nesting is a problem in SQL, but there is no easy way to achieve it . |
| Approach: | They propose a system which can handle nested logic queries without restrictions . they propose QUEST, which can cope with nesting queries without restriction . |
| Outcome: | The proposed system outperforms a baseline system by 11% accuracy. |
Atomic Self-Consistency for Better Long Form Generations (2024.emnlp-main)
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| Challenge: | Recent work has aimed to improve LLM generations by filtering out hallucinations, thereby improving the accuracy of the information in responses. |
| Approach: | They propose a technique that improves the recall of relevant information in an LLM. |
| Outcome: | The proposed technique improves the recall of relevant information in an LLM. |
QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations (2023.acl-long)
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| Challenge: | People express information needs with multiple preferences or constraints . modern retrieval systems struggle on such queries, a study finds . |
| Approach: | They construct a dataset of 3357 queries that map to a set of Wikipedia entities . they use crowd-sourced data to match constraints with evidence in documents . |
| Outcome: | The proposed dataset challenges models to match constraints mentioned in queries with evidence in documents and correctly perform various set operations. |