Computer Vision

FlashAttention-3, the latest release in the FlashAttention series, has been designed to address the inherent bottlenecks of the attention layer in Transformer architectures. These bottlenecks are crucial for the performance of large language models (LLMs) and...
One of the emerging challenges in artificial intelligence is whether next-token prediction can truly model human intelligence, particularly in planning and reasoning. Despite its extensive application in modern language models, this method might be inherently limited...

Enhancing Vision-Language Models: Addressing Multi-Object Hallucination and Cultural Inclusivity for Improved Visual Assistance in Diverse Contexts

The research on vision-language models (VLMs) has gained significant momentum, driven by their potential to revolutionize various applications, including visual assistance for visually impaired...

Meta 3D Gen: A state-of-the-art Text-to-3D Asset Generation Pipeline with Speed, Precision, and Superior Quality for Immersive Applications

Text-to-3D generation is an innovative field that creates three-dimensional content from textual descriptions. This technology is crucial in various industries, such as video games,...

Google Researchers Reveal Practical Insights into Knowledge Distillation for Model Compression

At the moment, many subfields of computer vision are dominated by large-scale vision models. Newly developed state-of-the-art models for tasks such as semantic segmentation,...

MG-LLaVA: An Advanced Multi-Modal Model Adept at Processing Visual Inputs of Multiple Granularities, Including Object-Level Features, Original-Resolution Images, and High-Resolution Data

Multi-modal Large Language Models (MLLMs) have various applications in visual tasks. MLLMs rely on the visual features extracted from an image to understand its...

Fal AI Introduces AuraSR: A 600M Parameter Upsampler Model Derived from the GigaGAN

In recent years, the field of artificial intelligence has witnessed significant advancements in image generation and enhancement techniques, as exemplified by models like Stable...

Comprehensive Analysis of The Performance of Vision State Space Models (VSSMs), Vision Transformers, and Convolutional Neural Networks (CNNs)

Deep learning models like Convolutional Neural Networks (CNNs) and Vision Transformers achieved great success in many visual tasks, such as image classification, object detection,...

CMU Researchers Propose In-Context Abstraction Learning (ICAL): An AI Method that Builds a Memory of Multimodal Experience Insights from Sub-Optimal Demonstrations and Human Feedback

Humans are versatile; they can quickly apply what they've learned from little examples to larger contexts by combining new and old information. Not only...

LongVA and the Impact of Long Context Transfer in Visual Processing: Enhancing Large Multimodal Models for Long Video Sequences

The field of research focuses on enhancing large multimodal models (LMMs) to process and understand extremely long video sequences. Video sequences offer valuable temporal...

NYU Researchers Introduce Cambrian-1: Advancing Multimodal AI with Vision-Centric Large Language Models for Enhanced Real-World Performance and Integration

Multimodal large language models (MLLMs) have become prominent in artificial intelligence (AI) research. They integrate sensory inputs like vision and language to create more...

NaRCan: A Video Editing AI Framework Integrating Diffusion Priors and LoRA Fine-Tuning to Produce High-Quality Natural Canonical Images

Video editing, a field of study that has garnered significant academic interest due to its interdisciplinary nature, impact on communication, and evolving technological landscape,...

Convolutional Kolmogorov-Arnold Networks (Convolutional KANs): An Innovative Alternative to the Standard Convolutional Neural Networks (CNNs)

Computer vision, one of the major areas of artificial intelligence, focuses on enabling machines to interpret and understand visual data. This field encompasses image...

Cephalo: A Series of Open-Source Multimodal Vision Large Language Models (V-LLMs) Specifically in the Context of Bio-Inspired Design

Materials science focuses on studying and developing materials with specific properties and applications. Researchers in this field aim to understand the structure, properties, and...

NuminaMath 7B TIR Released: Transforming Mathematical Problem-Solving with Advanced Tool-Integrated Reasoning and Python REPL...

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Numina has announced the release of its latest model, NuminaMath 7B TIR. This advanced language model is designed specifically for solving mathematical problems. The...

Tsinghua University Open Sources CodeGeeX4-ALL-9B: A Groundbreaking Multilingual Code Generation Model Outperforming Major Competitors...

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In a significant leap forward for the field of code generation, the Knowledge Engineering Group (KEG) and Data Mining team at Tsinghua University have...

InternLM2.5-7B-Chat: Open Sourcing Large Language Models with Unmatched Reasoning, Long-Context Handling, and Enhanced Tool...

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InternLM has unveiled its latest advancement in open large language models, the InternLM2.5-7B-Chat, available in GGUF format. This model is compatible with llama.cpp, an...

Jina AI Releases Jina Reranker v2: A Multilingual Model for RAG and Retrieval with...

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Jina AI has released the Jina Reranker v2 (jina-reranker-v2-base-multilingual), an advanced transformer-based model fine-tuned for text reranking tasks. This model is designed to significantly...

Google Releases Gemma 2 Series Models: Advanced LLM Models in 9B and 27B Sizes...

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Google has unveiled two new models in its Gemma 2 series: the 27B and 9B. These models showcase significant advancements in AI language processing,...

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