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This AI Paper Introduces BEST-STD (Spoken Term Detection): A Novel Bidirectional Mamba-Enhanced Speech Tokenization Framework for Efficient Spoken Term Detection Spoken term detection (STD) is a critical area in speech processing, enabling the identification of specific phrases or terms in large audio archives. This technology is extensively used in voice-based searches, transcription services, and multimedia indexing applications. By facilitating the retrieval of spoken content, STD plays a pivotal role in improving the accessibility and usability of audio data, especially in domains like podcasts, lectures, and broadcast media. Read the full article: https://lnkd.in/eaZTv-e4 Paper: https://lnkd.in/eiw2xS6Z

Enhanced IDS Framework with usfAD for Detecting Unknown Attacks Intrusion detection systems (IDS) encounter significant challenges in detecting zero-day or unknown cyberattacks, which are not included in the training data. These attacks do not have any identifiable pattern and cannot be easily detected by traditional techniques. The lack of annotated samples of attacks, the highly dynamic nature of attack methodologies, and the problem of high-dimensional datasets further pose a challenge to the problem. Read the full article: https://lnkd.in/eCcMZVhQ Paper: https://lnkd.in/eJ_JRmir

MBA-SLAM: A Novel AI Framework for Robust Dense Visual RGB-D SLAM, Implementing both an Implicit Radiance Fields Version and an Explicit Gaussian Splatting Version SLAM (Simultaneous Localization and Mapping) is one of the important techniques used in robotics and computer vision. It helps machines understand where they are and create a map of their surroundings. Motion-blurred images face difficulties in dense visual SLAM systems for two reasons: 1) Inaccurate pose estimation during tracking: Current photo-realistic dense visual SLAM algorithms rely on clear images to estimate camera positions by ensuring consistent brightness across views. Read the full article: https://lnkd.in/e-UFeKAn Paper: https://lnkd.in/eGQ6fQvd

Exploring Memory Options for Agent-Based Systems: A Comprehensive Overview Large language models (LLMs) have transformed the development of agent-based systems for good. However, managing memory in these systems remains a complex challenge. Memory mechanisms enable agents to maintain context, recall important information, and interact more naturally over extended periods. While many frameworks assume access to GPT or other proprietary APIs, the potential for local models to outperform GPT-3 or similar systems opens the door for more customized solutions. Read the full article: https://lnkd.in/eFEtjKeC

Researchers from NVIDIA and MIT Present SANA: An Efficient High-Resolution Image Synthesis Pipeline that Could Generate 4K Images from a Laptop Diffusion models have pulled ahead of others in text-to-image generation. With continuous research in this field over the past year, we can now generate high-resolution, realistic images that are indistinguishable from authentic images. However, with the increasing quality of the hyperrealistic images model, parameters are also escalating, and this trend results in high training and inference costs. Read the full article: https://lnkd.in/e-3Qbzk4 Paper: https://lnkd.in/ePQ6_spp

Red Teaming for AI: Strengthening Safety and Trust through External Evaluation Red teaming plays a pivotal role in evaluating the risks associated with AI models and systems. It uncovers novel threats, identifies gaps in current safety measures, and strengthens quantitative safety metrics. By fostering the development of new safety standards, it bolsters public trust and enhances the legitimacy of AI risk assessments. Read the full article: https://lnkd.in/eQ8M9myW Paper: https://lnkd.in/egxD5bCG

Composio Introduces AgentAuth: The Comprehensive Auth Solution Designed for AI Agents Building AI agents that interact with a variety of services presents significant challenges, particularly when it comes to managing authentication. Developers often face the frustration of setting up OAuth flows for Gmail, handling API keys for platforms like Linear, or configuring permissions across multiple services. These processes are complex enough for traditional applications, but AI agents add an additional layer of complexity. Read the full article: https://lnkd.in/ezP9aRVF

RhoFold+: A Deep Learning Framework for Accurate RNA 3D Structure Prediction from Sequences Predicting RNA 3D structures is critical for understanding its biological functions, advancing RNA-targeted drug discovery, and designing synthetic biology applications. However, RNA’s structural flexibility and the limited availability of experimentally resolved data pose challenges. Despite RNA’s importance in gene regulation, RNA-only structures represent less than 1% of the Data Bank, and traditional methods like X-ray crystallography and cryo-EM are slow and resource-intensive. Read the full article: https://lnkd.in/eBbMR2TQ Paper: https://lnkd.in/gS4qfdWF

SemiKong: An Open Source Foundation Model for Semiconductor Manufacturing Process Semiconductors are essential in powering various electronic devices and driving development across telecommunications, automotive, healthcare, renewable energy, and IoT industries. In semiconductor manufacturing and design, the two main phases, FEOL and BEOL, present unique challenges. LLMs are trained on vast amounts of text data using self-supervised learning techniques that can capture rich domain knowledge. Read the full article: https://lnkd.in/efDk-hfp Paper: https://lnkd.in/ez_pBGQp

Insight-V: Empowering Multi-Modal Models with Scalable Long-Chain Reasoning The capability of multimodal large language models (MLLMs) to enable complex long-chain reasoning that incorporates text and vision raises an even greater barrier in the realm of artificial intelligence. While text-centric reasoning tasks are being gradually advanced, multimodal tasks add additional challenges rooted in the lack of rich, comprehensive reasoning datasets and efficient training strategies. Read the full article: https://lnkd.in/eeyH9JTQ Paper: https://lnkd.in/eRRp4Awr