Researchers have introduced C3PO, a method for refining language models’ response behavior, strategically fine-tuning models to apply feedback relevantly while averting overgeneralization. It utilizes Direct Preference Optimization for in-scope data and Supervised Fine-Tuning losses for out-of-scope data, maintaining model integrity. Rigorous experiments show C3PO’s superior performance in incorporating feedback without overgeneralization, paving the way for…

The rise of Large Language Models (LLMs) has revolutionized text creation and computing interactions. However, challenges such as maintaining confidentiality and security persist. Microsoft’s AI Controller Interface (AICI) addresses these issues, surpassing traditional text-based APIs and offering granular control over LLM processing in the cloud. AICI supports security frameworks, application-specific functionalities, and diverse strategies for…

The introduction of AR and wearable AI gadgets is advancing human-computer interaction, allowing for highly contextualized AI assistants. Current multimodal AI assistants lack comprehensive contextual data, requiring a new approach. Meta’s Aria Everyday Activities (AEA) dataset, recorded with Project Aria glasses, offers a rich, four-dimensional view of daily activities, enhancing research and AI capabilities. For…

In 3D reconstruction, balancing visual quality and efficiency is crucial. Gaussian Splatting has limitations in handling high-frequency signals and sharp edges, impacting scene quality and memory usage. Generalized Exponential Splatting (GES) improves memory efficiency and scene representation, offering significant advancements in 3D modeling and rendering, promising impact across various 3D technology applications.

Generative deep learning models have transformed NLP, CV, speech processing, and TTS. Large language models demonstrate versatility in NLP, while pre-trained models excel in CV tasks. Amazon AGI’s BASE TTS, trained on extensive speech data, improves prosody rendering. It introduces novel discrete speech representations, promising significant progress in TTS. For more details, visit the Paper.

DataDreamer, an open-source Python library, aims to simplify the integration and use of large language models (LLMs). Developed by researchers from the University of Pennsylvania and the Vector Institute, it offers standardized interfaces to abstract complexity, streamline tasks like data generation and model fine-tuning, and improve the reproducibility and efficiency of LLM workflows.

Recent steps have been taken in the battle against deepfakes, including voluntary commitments from AI startups and big tech companies, as well as a call for a ban by civil society groups. However, challenges persist, such as technical feasibility, accountability across the deepfake pipeline, and the limited effectiveness of detection tools and watermarking. These issues…

Mixture-of-experts (MoE) models have transformed AI by dynamically assigning tasks to specialized components. Deployment in low-resource settings presents a challenge due to large size exceeding GPU memory. The University of Washington’s Fiddler optimizes MoE model deployment by efficiently coordinating CPU and GPU resources, achieving significant improvements in performance over traditional methods.

Transformer-based models like Gemini by Google and GPT models by OpenAI have shown exceptional performance in NLP and NLG, but struggle with length generalization. Google DeepMind researchers studied the Transformer’s ability to handle longer sequences and found that strategic selection of position encoding and data format can significantly enhance length generalization, enabling models to handle…