Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries | Paper Citation Record

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This paper cites GPT-4 Technical Report.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries GPT-4 Technical Report

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This paper cites nocaps: novel object captioning at scale.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries nocaps: novel object captioning at scale

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This paper cites Natural language interfaces to databases–an introduction.Natural language engineering, 1(1):29–81, 1995.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Natural language interfaces to databases–an introduction.Natural language engineering, 1(1):29–81, 1995

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Modeling score distributions in information retrieval

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries The multiplicative weights update method: a meta-algorithm and applications.Theory of computing, 8(1):121–164, 2012

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This paper cites Deep neural architecture for multi-modal retrieval based on joint embedding space for text and images.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Deep neural architecture for multi-modal retrieval based on joint embedding space for text and images

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This paper cites BEiT: BERT Pre-Training of Image Transformers.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries BEiT: BERT Pre-Training of Image Transformers

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This paper cites Lof: identifying density-based local outliers.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Lof: identifying density-based local outliers

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This paper cites Language Models are Few-Shot Learners.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Language Models are Few-Shot Learners

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This paper cites Large-scale content-based audio retrieval from text queries.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Large-scale content-based audio retrieval from text queries

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This paper cites Image search with text feedback by visiolin- guistic attention learning.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Image search with text feedback by visiolin- guistic attention learning

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This paper cites Palm: Scaling language modeling with pathways.Journal of Machine Learning Research, 24(240):1– 113, 2023.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Palm: Scaling language modeling with pathways.Journal of Machine Learning Research, 24(240):1– 113, 2023

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This paper cites On the inference of average precision from score distributions.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries On the inference of average precision from score distributions

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This paper cites Advanced generative ai methods for academic text summarization.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Advanced generative ai methods for academic text summarization

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This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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This paper cites Chameleon: Foundation models for fairness-aware multi-modal data augmentation to enhance coverage of minorities.Proceedings of the VLDB Endowment, 17(11):3470–3483, 2024.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Chameleon: Foundation models for fairness-aware multi-modal data augmentation to enhance coverage of minorities.Proceedings of the VLDB Endowment, 17(11):3470–3483, 2024

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Optimal aggregation algorithms for middleware

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This paper cites Eva: Exploring the limits of masked visual representation learning at scale.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Eva: Exploring the limits of masked visual representation learning at scale

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This paper cites Learning to rank for content-based image retrieval.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Learning to rank for content-based image retrieval

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This paper cites Tagging personal photos with transfer deep learning.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Tagging personal photos with transfer deep learning

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This paper cites Caltech 256, Apr 2022.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Caltech 256, Apr 2022

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Lvis: A dataset for large vocabulary instance segmentation

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This paper cites Query-aware locality- sensitive hashing for approximate nearest neighbor search.Proceedings of the VLDB Endow- ment, 9(1):1–12, 2015.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Query-aware locality- sensitive hashing for approximate nearest neighbor search.Proceedings of the VLDB Endow- ment, 9(1):1–12, 2015

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries A Survey on Locality Sensitive Hashing Algorithms and their Applications

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This paper cites Scaling up visual and vision-language representation learning with noisy text supervision.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Scaling up visual and vision-language representation learning with noisy text supervision

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Semantically- enhanced kernel canonical correlation analysis: a multi-label cross-modal retrieval.Multimedia Tools and Applications, 78:13169–13188, 2019

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Learning image embeddings using convolutional neural networks for improved multi-modal semantics

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Audio retrieval with natural language queries: A benchmark study.IEEE Transactions on Multimedia, 25:2675–2685, 2022

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries V oronoi-based k nearest neighbor search for spatial network databases

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Using synthetic data to train neural networks is model-based reasoning

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in Neural Information Processing Systems, 33:9459–9474, 2020

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Nalir: an interactive natural language interface for querying relational databases

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Cross-Modal Retrieval: A Systematic Review of Methods and Future Directions

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls.Advances in Neural Information Processing Systems, 36, 2024

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Blip: Bootstrapping language- image pre-training for unified vision-language understanding and generation

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries W2vv++ fully deep learning for ad-hoc video search

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Using LLM to select the right SQL Query from candidates

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Microsoft coco: Common objects in context

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Learning a recurrent residual fusion network for multimodal matching

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Mention Extraction and Linking for SQL Query Generation

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Unresolved cited work

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Query and keyframe representations for ad-hoc video search

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Senticap: Generating image descriptions with sentiments

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Howto100m: Learning a text-video embedding by watching hundred million narrated video clips

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Learning joint embedding with multimodal cues for cross-modal video-text retrieval

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Seesaw: interactive ad-hoc search over image databases.Proceedings of the ACM on Management of Data, 1(4):1–26, 2023

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Randomized algorithms.ACM Computing Surveys (CSUR), 28(1):33–37, 1996

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Learning and transferring mid- level image representations using convolutional neural networks

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries DINOv2: Learning Robust Visual Features without Supervision

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Composing object relations and attributes for image-text matching

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Learning transferable visual models from natural language supervision

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Observation d0493ea1-7e87-439a-836f-6e106a6499a1 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Hierarchical Text-Conditional Image Generation with CLIP Latents

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Observation 132c63d3-4d6b-47d1-b15f-b618eacbc94f · outbound

This paper cites A new approach to cross-modal multimedia retrieval.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries A new approach to cross-modal multimedia retrieval

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Observation 5cf954cf-f3db-4a44-9348-a400436f5255 · outbound

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Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Cola: A benchmark for compositional text-to-image retrieval.Advances in Neural Information Processing Systems, 36:46433–46445, 2023

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Observation 54fef369-921b-4784-a006-efc7a17d144f · outbound

This paper cites High- resolution image synthesis with latent diffusion models.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries High- resolution image synthesis with latent diffusion models

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Observation 61cb84e6-2eee-4f48-923f-686523a3c392 · outbound

This paper cites Multi-modal joint embedding for fashion product retrieval.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Multi-modal joint embedding for fashion product retrieval

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Observation 6a89fbc5-22b2-48e6-9840-fa3f50d72edd · outbound

This paper cites Coverage-based data-centric approaches for responsible and trustworthy ai.IEEE Data Eng.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Coverage-based data-centric approaches for responsible and trustworthy ai.IEEE Data Eng

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Observation 1628244f-5705-4288-81be-a87172f5b3de · outbound

This paper cites Flava: A foundational language and vision alignment model.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Flava: A foundational language and vision alignment model

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Observation ba62b6fc-fc0c-49de-be79-5ba96d9504f1 · outbound

This paper cites Data Augmentation Using GANs.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Data Augmentation Using GANs

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Observation 3834c631-7f7f-478e-8e31-5ffc135ace34 · outbound

This paper cites Interacting- enhancing feature transformer for cross-modal remote-sensing image and text retrieval.IEEE Transactions on Geoscience and Remote Sensing, 61:1–15, 2023.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Interacting- enhancing feature transformer for cross-modal remote-sensing image and text retrieval.IEEE Transactions on Geoscience and Remote Sensing, 61:1–15, 2023

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Observation dbbc7171-f808-47df-a0ad-6c6c07c49433 · outbound

This paper cites Winoground: Probing vision and language models for visio-linguistic compositionality.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Winoground: Probing vision and language models for visio-linguistic compositionality

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Observation 840cb99b-1bc7-408b-a4ef-c713959af5d5 · outbound

This paper cites Learning Language-Visual Embedding for Movie Understanding with Natural-Language.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Learning Language-Visual Embedding for Movie Understanding with Natural-Language

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Observation bd8c26fd-7865-4ca7-b5de-0ed6363d70a5 · outbound

This paper cites Training deep networks with synthetic data: Bridging the reality gap by domain randomization.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Training deep networks with synthetic data: Bridging the reality gap by domain randomization

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Observation 4db8cbd5-d230-464c-93f7-9d1c5948e843 · outbound

This paper cites Codexdb: Synthesizing code for query processing from natural language instructions using gpt-3 codex.Proceedings of the VLDB Endowment, 15(11):2921–2928, 2022.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Codexdb: Synthesizing code for query processing from natural language instructions using gpt-3 codex.Proceedings of the VLDB Endowment, 15(11):2921–2928, 2022

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Observation 2a11ac16-5a54-40f7-9e4b-2cf2103b15fd · outbound

This paper cites Demonstrating gpt-db: Generating query-specific and customizable code for sql processing with gpt-4.Proceedings of the VLDB Endowment, 16(12):4098–4101, 2023.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Demonstrating gpt-db: Generating query-specific and customizable code for sql processing with gpt-4.Proceedings of the VLDB Endowment, 16(12):4098–4101, 2023

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 56c70c32-b6a1-4f4a-8a01-6f232292a81d · outbound

This paper cites Diffusion Models for Tabular Data Imputation and Synthetic Data Generation.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Diffusion Models for Tabular Data Imputation and Synthetic Data Generation

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Observation 8817a9e3-cdea-4f7b-90ae-a7f896f402ed · outbound

This paper cites Image-text cross- modal retrieval via modality-specific feature learning.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Image-text cross- modal retrieval via modality-specific feature learning

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f3330211-bd5e-4242-952e-72fab252c0f0 · outbound

This paper cites Cluster-sensitive structured correlation analysis for web cross-modal retrieval.Neurocomputing, 168:747–760, 2015.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Cluster-sensitive structured correlation analysis for web cross-modal retrieval.Neurocomputing, 168:747–760, 2015

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Observation b7c8f82b-1492-498a-bb58-b6a967587808 · outbound

This paper cites Cross- modal retrieval: a systematic review of methods and future directions.Proceedings of the IEEE, 2025.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Cross- modal retrieval: a systematic review of methods and future directions.Proceedings of the IEEE, 2025

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Observation d018c000-e9ef-46fc-a56f-9e8fa842977a · outbound

This paper cites Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.Advances in neural information processing systems, 33:5776–5788, 2020.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.Advances in neural information processing systems, 33:5776–5788, 2020

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Observation 003373c8-4e1d-4e0e-9d04-f9b2e30ebb8b · outbound

This paper cites Convnext v2: Co-designing and scaling convnets with masked autoencoders.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Convnext v2: Co-designing and scaling convnets with masked autoencoders

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Observation 306cb27b-073f-4b70-928f-6cc02880127b · outbound

This paper cites Improving text-audio retrieval by text-aware attention pooling and prior matrix revised loss.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Improving text-audio retrieval by text-aware attention pooling and prior matrix revised loss

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Observation d162a88a-9f7a-42dc-b04d-459d9d2dc2c2 · outbound

This paper cites Regnet: self-regulated network for image classification.IEEE Transactions on Neural Networks and Learning Systems, 34(11):9562–9567, 2022.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Regnet: self-regulated network for image classification.IEEE Transactions on Neural Networks and Learning Systems, 34(11):9562–9567, 2022

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Observation 78bd2647-525b-4f47-aab9-15c6ed938557 · outbound

This paper cites Re- thinking label-wise cross-modal retrieval from a semantic sharing perspective.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Re- thinking label-wise cross-modal retrieval from a semantic sharing perspective

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Observation 8bb25eb5-e961-4073-bc13-0960d3a6882b · outbound

This paper cites Saliencycut: Augmenting plausible anomalies for anomaly detection.Pattern Recognition, 153:110508, 2024.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Saliencycut: Augmenting plausible anomalies for anomaly detection.Pattern Recognition, 153:110508, 2024

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5db307f8-62f4-4c37-abaa-198e90b28e8b · outbound

This paper cites Data structures and algorithms for nearest neighbor search in general metric spaces.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Data structures and algorithms for nearest neighbor search in general metric spaces

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c626ba84-4d8a-4ea7-9a66-335e54ffb417 · outbound

This paper cites Bdd100k: A diverse driving dataset for heterogeneous mul- titask learning.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Bdd100k: A diverse driving dataset for heterogeneous mul- titask learning

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Observation 093a73e4-9905-4024-9955-534654d2cf36 · outbound

This paper cites Text-to-image Diffusion Models in Generative AI: A Survey.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Text-to-image Diffusion Models in Generative AI: A Survey

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Observation 3abe202b-f128-409b-bc8c-49c9827b9d5d · outbound

This paper cites Interactive retrieval based on faceted feedback.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Interactive retrieval based on faceted feedback

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Observation a90a289f-4419-4615-b211-270d0e889d74 · outbound

This paper cites Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions

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Observation b712a92d-adc2-4146-be6d-90990570a4cd · outbound

This paper cites Recognize anything: A strong image tagging model.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Recognize anything: A strong image tagging model

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Observation fc589fc1-19d9-4da2-bf5c-ca6cce20f353 · outbound

This paper cites Relevance feedback in image retrieval: A comprehen- sive review.Multimedia systems, 8:536–544, 2003.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Relevance feedback in image retrieval: A comprehen- sive review.Multimedia systems, 8:536–544, 2003

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:13:50.872818Z

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Observation dc3c0932-c0c9-4094-a893-baaac7a13db1 · outbound

This paper cites complex.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries complex

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Resolution: verified exact; raw_fallback, observed 2026-08-12T05:13:50.487397Z

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Observation 4707a352-3bb5-4c85-84f4-3cab6ec2a4dd · outbound

This paper cites hard categories.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries hard categories

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:13:50.861769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6f59687e-ec73-4c55-b87b-0b3e615186a7 · outbound

This paper cites However, while CLIP (in our clip-vit-base-patch32 variant) uses a Vision Transformer for image encoding, ALIGN typically uses a CNN image encoder along with a Transformer for text.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries However, while CLIP (in our clip-vit-base-patch32 variant) uses a Vision Transformer for image encoding, ALIGN typically uses a CNN image encoder along with a Transformer for text

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:13:50.850455Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 44862ebd-8d22-4ba6-b439-a2e7fadbccf4 · outbound

This paper cites an unresolved cited work.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Unresolved cited work

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Resolution: unresolved; raw_fallback, observed 2026-08-12T05:13:50.839036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e2dd76e6-d762-4d52-97ba-25e3efecd724 · outbound

This paper cites The generated captions are then transformed into embeddings with MiniLM [72]30, a robust text encoder widely adopted in industrial applications.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries The generated captions are then transformed into embeddings with MiniLM [72]30, a robust text encoder widely adopted in industrial applications

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:13:50.827473Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f09832f3-108a-4da3-ac67-d4bbe1e21ff6 · outbound

This paper cites Its diverse object classes make it a useful benchmark for assessing the robustness of detection and retrieval models.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Its diverse object classes make it a useful benchmark for assessing the robustness of detection and retrieval models

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:13:50.815240Z

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Observation 08f3106d-0611-4934-8d62-bee28d29f3eb · outbound

This paper cites Its comprehensive annotations and varied scene compositions provide a challenging testbed.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Its comprehensive annotations and varied scene compositions provide a challenging testbed

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:13:50.802825Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c9a1bc4f-db46-46be-8cbc-9beef33b8461 · outbound

This paper cites Its focus on rare and fine-grained objects is critical for evaluating retrieval performance on less frequent classes.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Its focus on rare and fine-grained objects is critical for evaluating retrieval performance on less frequent classes

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:13:50.789721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fc3f5d7f-ec0d-42ed-8161-fe631ca9a18a · outbound

This paper cites an unresolved cited work.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Unresolved cited work

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Resolution: unresolved; raw_fallback, observed 2026-08-12T05:13:50.775213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2e1f6167-9cf9-404f-8ea5-aa75c944c7d0 · outbound

This paper cites an unresolved cited work.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Unresolved cited work

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Resolution: unresolved; raw_fallback, observed 2026-08-12T05:13:50.761918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 28c9aa30-21d8-41f9-bcda-a99997e02d9c · outbound

This paper cites This dataset challenges models to accurately map nuanced language to the corresponding image, serving as a stringent test of fine-grained retrieval performance.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries This dataset challenges models to accurately map nuanced language to the corresponding image, serving as a stringent test of fine-grained retrieval performance

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:13:50.750959Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7e9add9b-2666-45da-902b-a29577210573 · outbound

This paper cites It is crucial for evaluating a model’s ability to handle zero-shot retrieval on images containing objects not commonly found in standard captioning datasets.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries It is crucial for evaluating a model’s ability to handle zero-shot retrieval on images containing objects not commonly found in standard captioning datasets

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:13:50.739954Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6b6530b0-6158-4239-81cb-78b93666f499 · outbound

This paper cites Left is better,.

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries Left is better,

Reference 97

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T05:13:50.728272Z

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