DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding | Paper Citation Record

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This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Llama 2: Open Foundation and Fine-Tuned Chat Models

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This paper cites GPT-4 Technical Report.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding GPT-4 Technical Report

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This paper cites Retrieval-augmented generation for knowledge- intensive nlp tasks,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Retrieval-augmented generation for knowledge- intensive nlp tasks,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding REALM: Retrieval-augmented language model pre-training,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Retrieval-Augmented Generation for Large Language Models: A Survey

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This paper cites Dense passage retrieval for open-domain question answering,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Dense passage retrieval for open-domain question answering,

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This paper cites Leveraging passage retrieval with gener- ative models for open domain question answering,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Leveraging passage retrieval with gener- ative models for open domain question answering,

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This paper cites Rag-anything: All-in-one rag framework,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Rag-anything: All-in-one rag framework,

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This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding From Local to Global: A Graph RAG Approach to Query-Focused Summarization

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This paper cites G-Retriever: Retrieval-augmented generation for textual graph understanding and question answering,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding G-Retriever: Retrieval-augmented generation for textual graph understanding and question answering,

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This paper cites LayoutLMv3: Pre- training for document ai with unified text and image masking,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding LayoutLMv3: Pre- training for document ai with unified text and image masking,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Ocr-free document understanding transformer,

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This paper cites Nougat: Neural Optical Understanding for Academic Documents.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Nougat: Neural Optical Understanding for Academic Documents

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This paper cites Docvqa: A dataset for vqa on document images,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Docvqa: A dataset for vqa on document images,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Towards vqa models that can read,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Visual instruction tuning,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models,

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This paper cites Flamingo: a visual language model for few-shot learning,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Flamingo: a visual language model for few-shot learning,

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This paper cites Instructblip: Towards general-purpose vision-language models with instruc- tion tuning,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Instructblip: Towards general-purpose vision-language models with instruc- tion tuning,

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This paper cites Llms for knowledge graph construction and reasoning: Recent capabilities and future opportunities,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Llms for knowledge graph construction and reasoning: Recent capabilities and future opportunities,

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This paper cites Mitigating object hallucinations in large vision-language mod- els through visual contrastive decoding,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Mitigating object hallucinations in large vision-language mod- els through visual contrastive decoding,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Woodpecker: Hallucination correction for multimodal large language models,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Hallusionbench: An advanced diagnostic suite for entangled language halluci- nation and visual illusion in large vision-language models,

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This paper cites Evaluating object hallucination in large vision-language models,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Evaluating object hallucination in large vision-language models,

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This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding An image is worth 16x16 words: Transformers for image recognition at scale,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Swin transformer: Hierarchical vision transformer using shifted windows,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Flashattention: Fast and memory-efficient exact attention with io-awareness,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Vision trans- formers need registers,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Efficient streaming language models with attention sinks,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding H 2O: Heavy- hitter oracle for efficient generative inference of large language models,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding MMGraphRAG: Bridging Vision and Language with Interpretable Multimodal Knowledge Graphs

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding MegaRAG: Multimodal Knowledge Graph-Based Retrieval Augmented Generation

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Image cropping with spatial-aware feature and rank consistency,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Reliable and efficient image cropping: A grid anchor based approach,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corpora

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Chartqa: A benchmark for question answering about charts with visual and logical reasoning,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding Slidevqa: A dataset for document visual question an- swering on multiple images,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding TabFact: A large-scale dataset for table-based fact verification,

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DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment

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