​[[{“value”:” In the evolving landscape of artificial intelligence and natural language processing, utilizing large language models (LLMs) has become increasingly prevalent. However, one of the challenges that persist in this domain is enabling these models to engage in role-play effectively. This work requires a deep… Read More »Alibaba Researchers Introduce Ditto: A Revolutionary Self-Alignment Method to Enhance Role-Play in Large Language Models Beyond GPT-4 Standards Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:”Machine learning (ML) models are fundamentally shaped by data, and building inclusive ML systems requires significant considerations around how to design representative datasets. Yet, few novice-oriented ML modeling tools are designed to foster hands-on learning of dataset design practices, including how to design for data… Read More »Co-ML: Collaborative Machine Learning Model Building for Developing Dataset Design Practices Apple Machine Learning Research

​Recent advances in deep learning and automatic speech recognition (ASR) have enabled the end-to-end (E2E) ASR system and boosted its accuracy to a new level. The E2E systems implicitly model all conventional ASR components, such as the acoustic model (AM) and the language model (LM),… Read More »Acoustic Model Fusion for End-to-end Speech Recognition Apple Machine Learning Research

​Tracking biosignals is crucial for monitoring wellness and preempting the development of severe medical conditions. Today, wearable devices can conveniently record various biosignals, creating the opportunity to monitor health status without disruption to one’s daily routine. Despite the widespread use of wearable devices and existing… Read More »Large-scale Training of Foundation Models for Wearable Biosignals Apple Machine Learning Research

​Representations from models such as Bidirectional Encoder Representations from Transformers (BERT) and Hidden units BERT (HuBERT) have helped to achieve state-of-the-art performance in dimensional speech emotion recognition. Both HuBERT, and BERT models generate fairly large dimensional representations, and such models were not trained with emotion… Read More »Investigating Salient Representations and Label Variance Modeling in Dimensional Speech Emotion Analysis Apple Machine Learning Research

​We study differentially private stochastic convex optimization (DP-SCO) under user-level privacy where each user may hold multiple data items. Existing work for user-level DP-SCO either requires super-polynomial runtime or requires number of users that grows polynomially with the dimensionality of the problem. We develop new… Read More »User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates Apple Machine Learning Research

​[[{“value”:” Language models (LMs) often struggle with reasoning tasks like math or coding, particularly in low-resource languages. This challenge arises because LMs are primarily trained on data from a few high-resource languages, leaving low-resource languages underrepresented.  Previously, researchers have addressed this by continually training English-centric… Read More »Researchers from KAIST and the University of Washington have introduced ‘LANGBRIDGE’: A Zero-Shot AI Approach to Adapt Language Models for Multilingual Reasoning Tasks without Multilingual Supervision Mohammad Arshad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Recent advances in language models showcase impressive zero-shot voice conversion (VC) capabilities. Nevertheless, prevailing VC models rooted in language models usually utilize offline conversion from source semantics to acoustic features, necessitating the entirety of the source speech and limiting their application to real-time scenarios.… Read More »This AI Paper from China Introduces StreamVoice: A Novel Language Model-Based Zero-Shot Voice Conversion System Designed for Streaming Scenarios Janhavi Lande Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Vision-language models (VLMs) are increasingly prevalent, offering substantial advancements in AI-driven tasks. However, one of the most significant limitations of these advanced models, including prominent ones like GPT-4V, is their constrained spatial reasoning capabilities. Spatial reasoning involves understanding objects’ positions in three-dimensional space and… Read More »Google AI Research Proposes SpatialVLM: A Data Synthesis and Pre-Training Mechanism to Enhance Vision-Language Model VLM Spatial Reasoning Capabilities Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” There is a need to build systems that can respond to user inputs, remember past interactions, and make decisions based on that history. This requirement is crucial for creating applications that behave more like intelligent agents, capable of maintaining a conversation, remembering past context,… Read More »Meet LangGraph: An AI Library for Building Stateful, Multi-Actor Applications with LLMs Built on Top of LangChain Niharika Singh Artificial Intelligence Category – MarkTechPost