SOTAVerified

Natural Language Queries

Papers

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Showing 126–150 of 337 papers

TitleStatusHype
Constraint-based Multi-hop Question Answering with Knowledge Graph—0
Case-based Reasoning for Natural Language Queries over Knowledge Bases—0
A Japanese Chess Commentary Corpus—0
Large Language Models as Narrative-Driven Recommenders—0
Learning Joint Representations of Videos and Sentences with Web Image Search—0
DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections—0
Do Audio-Language Models Understand Linguistic Variations?—0
Can Language Models Act as Knowledge Bases at Scale?—0
Diverse Parallel Data Synthesis for Cross-Database Adaptation of Text-to-SQL Parsers—0
Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries—0
Bring Remote Sensing Object Detect Into Nature Language Model: Using SFT Method—0
A Socratic RAG Approach to Connect Natural Language Queries on Research Topics with Knowledge Organization Systems—0
Leveraging Chemistry Foundation Models to Facilitate Structure Focused Retrieval Augmented Generation in Multi-Agent Workflows for Catalyst and Materials Design—0
DGMO: Training-Free Audio Source Separation through Diffusion-Guided Mask Optimization—0
DFIN-SQL: Integrating Focused Schema with DIN-SQL for Superior Accuracy in Large-Scale Databases—0
Bridging the Semantic Gaps: Improving Medical VQA Consistency with LLM-Augmented Question Sets—0
Automating Pharmacovigilance Evidence Generation: Using Large Language Models to Produce Context-Aware SQL—0
ACE: A Generative Cross-Modal Retrieval Framework with Coarse-To-Fine Semantic Modeling—0
Knowledge Graph Question Answering via SPARQL Silhouette Generation—0
DB-Explore: Automated Database Exploration and Instruction Synthesis for Text-to-SQL—0
Bridging the Gap: Enabling Natural Language Queries for NoSQL Databases through Text-to-NoSQL Translation—0
Language-based Audio Retrieval with Co-Attention Networks—0
Language-Guided Audio-Visual Source Separation via Trimodal Consistency—0
Leveraging LLMs to Enable Natural Language Search on Go-to-market Platforms—0
Beyond Fine-Tuning: Effective Strategies for Mitigating Hallucinations in Large Language Models for Data Analytics—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EgoVideoR@1 Mean(0.3 and 0.5)23.68—Unverified
2DeCafNet-100%R@1 Mean(0.3 and 0.5)18.86—Unverified
3DeCafNet-50%R@1 Mean(0.3 and 0.5)17.93—Unverified
4RGNetR@1 Mean(0.3 and 0.5)16.55—Unverified
5DeCafNet-50% (no NaQ)R@1 Mean(0.3 and 0.5)15.32—Unverified
6InternVideoR@1 Mean(0.3 and 0.5)13.26—Unverified
7EgoVLPv2R@1 IoU=0.312.95—Unverified
8UniMD+Sync.R@1 Mean(0.3 and 0.5)12.11—Unverified
9ReLER@ZJU-AlibabaR@1 Mean(0.3 and 0.5)10.52—Unverified
10EgoVLPR@1 Mean(0.3 and 0.5)8.35—Unverified