Classifying the entirety of SafeDocs, Santiago Pedroza utilized a combination of LLMs, Embeddings Models, XGBoost, and LinearRegressors, achieving a significant improvement in accuracy with XGBoost embeddings model reaching 85.26% after hyperparameter tuning. SafeDocsDARPA SafeDocs program
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models
xGen-MM (BLIP-3) introduces a comprehensive framework for Large Multimodal Models (LMMs), featuring curated datasets, a training recipe, model architectures, and a suite of LMMs, expanding the Salesforce xGen initiative.
[R] JPEG-LM: LLMs as Image Generators with Canonical Codec Representations
JPEG-LM leverages canonical codec representations like JPEG for image generation, outperforming traditional pixel-based and vector quantization methods in efficiency and effectiveness.
[R] Prompt Cache: Modular Attention Reuse for Low-Latency Inference
Prompt Cache accelerates LLM inference by precomputing and caching attention states of frequently occurring text segments, enabling rapid reuse for new prompts.
LLMs know more than what they say
Latent Space Readout (LSR) techniques applied to Large Language Models (LLMs) enhance evaluation accuracy for hallucination detection and numeric scoring, outperforming traditional fine-tuning methods with significantly fewer examples of human feedback.
Music recommendation system using transformer models
Google Research introduces a music recommendation system employing Transformer models to analyze the sequence of user actions, enhancing personalization based on current context.
TextCAVs: Debugging vision models using text
TextCAVs introduces a novel method for creating concept activation vectors ( CAVs) using vision-language models like CLIP, leveraging text descriptions instead of image exemplars for concept explanation.
AI Chases the Storm: New NVIDIA Research Boosts Weather Prediction, Climate Simulation
NVIDIA's new generative AI model, StormCast, enhances weather prediction by emulating high-fidelity atmospheric dynamics, crucial for disaster planning amid increasing extreme weather events.
🤗Deploy Meta Llama 3.1 405B on Google Cloud Vertex AI
Deploying Meta Llama 3.1 405B on Google Cloud Vertex AI involves using a pre-built Hugging Face Deep Learning Container (DLC) for real-time online predictions, with the model being a FP8 quantized variant for efficient deployment on A3 nodes equipped with 8 x H100 NVIDIA GPUs.
SC-Rec: Enhancing Generative Retrieval with Self-Consistent Reranking for~Sequential Recommendation
SC-Rec introduces a novel reranking strategy in recommendation systems, leveraging Language Models (LMs) to enhance generative retrieval by integrating diverse preference knowledge from varied item indices and prompt templates.
PatUntrack: Automated Generating Patch Examples for Issue Reports without Tracked Insecure Code
PatUntrack proposes an innovative approach to automatically generate patch examples for issue reports (IRs) lacking tracked insecure code, leveraging Large Language Models (LLMs) to analyze vulnerabilities.
A Mechanistic Interpretation of Syllogistic Reasoning in Auto-Regressive Language Models
The study introduces a methodology for circuit discovery in auto-regressive Language Models (LMs), aiming to separate content-independent reasoning from world knowledge, enhancing our understanding of LMs' internal dynamics.
Context-Aware Assistant Selection for Improved Inference Acceleration with Large Language Models
Context-aware assistant selection significantly improves inference acceleration in large language models by leveraging multiple draft models to guide a larger target model, enhancing performance across various domains.