​[[{“value”:” Despite the significant strides in large language models (LLMs) such as ChatGPT, Llama2, Vicuna, and Gemini, they grapple with safety issues. This paper introduces a novel safety-aware decoding technique, SafeDecoding, which aims to protect LLMs from jailbreak attacks, a pressing concern evidenced by LLMs… Read More »Meet SafeDecoding: A Novel Safety-Aware Decoding AI Strategy to Defend Against Jailbreak Attacks Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​Hand gesture recognition is becoming a more prevalent mode of human-computer interaction, especially as cameras proliferate across everyday devices. Despite continued progress in this field, gesture customization is often underexplored. Customization is crucial since it enables users to define and demonstrate gestures that are more… Read More »Vision-Based Hand Gesture Customization from a Single Demonstration Apple Machine Learning Research

​As the repository of publicly available pre-trained vision foundation models (VFMs) — such as CLIP, DINOv2, and SAM — grows, users face challenges in storage, memory, and computational efficiency when deploying multiple models concurrently. To address these concerns, we introduce a unique approach that merges… Read More »Merge Vision Foundation Models via Multi-Task Distillation Apple Machine Learning Research

​[[{“value”:”*=Equal Contributors Personal devices have adopted diverse authentication methods, including biometric recognition and passcodes. In contrast, headphones have limited input mechanisms, depending solely on the authentication of connected devices. We present Moonwalk, a novel method for passive user recognition utilizing the built-in headphone accelerometer. Our… Read More »Moonwalk: Advancing Gait-Based User Recognition on Wearable Devices with Metric Learning Apple Machine Learning Research

​[[{“value”:” In the domain of biotechnology, the intersection of machine learning and genomics has sparked a revolutionary paradigm, particularly in the modeling of DNA sequences. This interdisciplinary approach addresses the intricate challenges posed by genomic data, which include understanding long-range interactions within the genome, the… Read More »This AI Paper from Cornell Proposes Caduceus: Deciphering the Best Tokenization Strategies for Enhanced NLP Models Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The quest to enhance learning experiences is unending in the fast-evolving landscape of educational technology, with mathematics standing out as a particularly challenging domain. Previous teaching methods, while foundational, often need to catch up in catering to students’ diverse needs, especially when it comes… Read More »Microsoft AI Research Introduces Orca-Math: A 7B Parameters Small Language Model (SLM) Created by Fine-Tuning the Mistral 7B Model Muhammad Athar Ganaie Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Developing and refining Large Language Models (LLMs) has become a focal point of cutting-edge research in the rapidly evolving field of artificial intelligence, particularly in natural language processing. These sophisticated models, designed to comprehend, generate, and interpret human language, rely on the breadth and… Read More »Decoding the DNA of Large Language Models: A Comprehensive Survey on Datasets, Challenges, and Future Directions Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In the ever-evolving field of computational linguistics, the quest for models that can seamlessly generate human-like text has led researchers to explore innovative techniques beyond traditional frameworks. One of the most promising avenues in recent times has been the exploration of diffusion models, previously… Read More »Microsoft Researchers Propose A Novel Text Diffusion Model (TREC) that Mitigates the Degradation with Reinforced Conditioning and the Misalignment by Time-Aware Variance Scaling Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Training large language models (LLMs) has posed a significant challenge due to their memory-intensive nature. The conventional approach of reducing memory consumption by compressing model weights often leads to performance degradation. However, a novel method, Gradient Low-Rank Projection (GaLore), by researchers from the California… Read More »Revolutionizing LLM Training with GaLore: A New Machine Learning Approach to Enhance Memory Efficiency without Compromising Performance Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The inference method is crucial for NLP models in subword tokenization. Methods like BPE, WordPiece, and UnigramLM offer distinct mappings, but their performance differences must be better understood. Implementations like Huggingface Tokenizers often need to be clearer or limit inference choices, complicating compatibility with… Read More »Unlocking the Best Tokenization Strategies: How Greedy Inference and SaGe Lead the Way in NLP Models Mohammad Asjad Artificial Intelligence Category – MarkTechPost