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Found 11 papers, 5 papers with code
A Research Framework for Understanding Education-Occupation Alignment with NLP Techniques
Understanding the gaps between job requirements and university curricula is crucial for improving student success and institutional effectiveness in higher education.
A Blueprint Architecture of Compound AI Systems for Enterprise
Large Language Models (LLMs) have showcased remarkable capabilities surpassing conventional NLP challenges, creating opportunities for use in production use cases.
Retrieval Helps or Hurts? A Deeper Dive into the Efficacy of Retrieval Augmentation to Language Models
We demonstrate the efficacy of our finer-grained metric and insights through an adaptive retrieval system that selectively employs retrieval and recall based on the frequencies of entities and relations in the question.
XATU: A Fine-grained Instruction-based Benchmark for Explainable Text Updates
Text editing is a crucial task of modifying text to better align with user intents.
Why are NLP Models Fumbling at Elementary Math? A Survey of Deep Learning based Word Problem Solvers
From the latter half of the last decade, there has been a growing interest in developing algorithms for automatically solving mathematical word problems (MWP).
A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases
Specifically, our benchmark is a temporal question answering dataset with the following advantages: (a) it is based on Wikidata, which is the most frequently curated, openly available knowledge base, (b) it includes intermediate sparql queries to facilitate the evaluation of semantic parsing based approaches for KBQA, and (c) it generalizes to multiple knowledge bases: Freebase and Wikidata.
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases
In addition, to demonstrate extensi-bility to additional reasoning types we evaluate on multi-hopreasoning datasets and a new Temporal KBQA benchmarkdataset on Wikidata, namedTempQA-WD1, introduced in thispaper.
LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking
Entity linking (EL), the task of disambiguating mentions in text by linking them to entities in a knowledge graph, is crucial for text understanding, question answering or conversational systems.
Leveraging Abstract Meaning Representation for Knowledge Base Question Answering
Knowledge base question answering (KBQA)is an important task in Natural Language Processing.
Low-resource Deep Entity Resolution with Transfer and Active Learning
Recent adaptation of deep learning methods for ER mitigates the need for dataset-specific feature engineering by constructing distributed representations of entity records.
KOGNAC: Efficient Encoding of Large Knowledge Graphs
We propose KOGNAC, a dictionary-encoding algorithm designed to improve SPARQL querying with a judicious combination of statistical and semantic techniques.
