ViDoRe V3
PulseAugur coverage of ViDoRe V3 — every cluster mentioning ViDoRe V3 across labs, papers, and developer communities, ranked by signal.
4 day(s) with sentiment data
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New method enhances visual evidence use in multimodal RAG systems
Researchers have developed a new method called Loud and Clear (LoC) to improve how multimodal document retrieval-augmented generation (RAG) systems utilize visual information. The study found that existing methods under…
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New method recovers retrieval quality lost to document vector compression
Researchers have developed a method to improve the quality of compressed document vectors in late-interaction models. By learning a global linear correction, the method can recover retrieval quality lost due to aggressi…
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Perplexity releases new embedding models, achieves SOTA on benchmarks
Perplexity has released two new late-interaction embedding models, pplx-embed-v2-late, which can retrieve text, images, and pages within a shared embedding space. These models achieve frontier performance and are availa…
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Visual document retrieval indices vulnerable to reconstruction attacks
Researchers have discovered a significant vulnerability in multi-vector visual document retrieval systems, where stored indices can be used to reconstruct original documents. The study, published on arXiv, demonstrates …
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Cohere releases Embed 5 with multimodal capabilities and dual-tier approach
Cohere has launched Embed 5, a new family of embedding models designed for enterprise search, RAG, and agentic retrieval. The model comes in two tiers: Embed 5 Pro for maximum quality and Embed 5 Fast for lower latency …
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H Company releases NeoMME, a single-tower multimodal encoder family
H Company has introduced NeoMME, a new family of multimodal encoders designed for efficiency. These models, available in 260M and 800M parameter sizes, eliminate the need for separate vision towers and causal decoders, …
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Hugging Face unveils efficient multimodal encoder NeoMME, study favors encoders for Indic NER
Hugging Face has introduced NeoMME, a new family of multilingual multimodal encoders designed for efficiency. Unlike many generative models, NeoMME uses a single bidirectional Transformer to process both text and image …
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New SearchWiki framework learns to navigate knowledge wikis for active information seeking
Researchers have developed SearchWiki, a framework designed to synthesize a corpus into a structured, navigable knowledge wiki. This system trains an agent, WikiResearcher-9B, to actively seek information through multi-…
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New frameworks enhance multimodal document retrieval accuracy and efficiency · 4 sources tracked
Researchers have developed new frameworks for multimodal document retrieval to improve question-answering accuracy over visually rich documents. MIDR shifts multimodal reasoning to index time, achieving significant gain…
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PULSAR system enhances enterprise visual document search with pooled indexing
A new research paper introduces PULSAR, a vision-first retrieval system designed for enterprise visual document RAG. Deployed at Mubadala Investment Company, PULSAR uses a pooled, late-interaction index to efficiently s…
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New method enhances VLM document layout understanding
Researchers have developed a new method to improve how Vision-Language Models (VLMs) understand document layouts, particularly for documents with structures not seen during training. The approach pre-resolves layout inf…