Notizie
Sampling Without Data is Now Scalable: Meta AI Releases Adjoint Sampling for Reward-Driven Generative Modeling
Data Scarcity in Generative Modeling Generative models traditionally rely on large, high-quality datasets to produce...
Sam Altman calls for ‘AI privilege’ as OpenAI clarifies court order to retain temporary and deleted ChatGPT sessions
Should talking to an AI chatbot be protected and privileged information, like talking to a...
Salesforce AI Releases Moirai 2.0: Salesforce’s Latest Time Series Foundation Model Built on a Decoder‑only Transformer Architecture
Salesforce AI Research has unveiled Moirai 2.0, the latest advancement in the world of time...
Salesforce AI Releases BLIP3-o: A Fully Open-Source Unified Multimodal Model Built with CLIP Embeddings and Flow Matching for Image Understanding and Generation
Multimodal modeling focuses on building systems to understand and generate content across visual and textual...
Salesforce AI Introduces CRMArena-Pro: The First Multi-Turn and Enterprise-Grade Benchmark for LLM Agents
AI agents powered by LLMs show great promise for handling complex business tasks, especially in...
Sakana AI Released ShinkaEvolve: An Open-Source Framework that Evolves Programs for Scientific Discovery with Unprecedented Sample-Efficiency
Table of contents What problem is it actually solving? Does the sample-efficiency claim hold beyond...
Sakana AI Introduces Text-to-LoRA (T2L): A Hypernetwork that Generates Task-Specific LLM Adapters (LoRAs) based on a Text Description of the Task
Transformer models have significantly influenced how AI systems approach tasks in natural language understanding, translation...
SafeMT: Multi-turn Safety for Multimodal Language Models
arXiv:2510.12133v1 Announce Type: new Abstract: With the widespread use of multi-modal Large Language models (MLLMs)...
SAEMark: Multi-bit LLM Watermarking with Inference-Time Scaling
arXiv:2508.08211v1 Announce Type: new Abstract: Watermarking LLM-generated text is critical for content attribution and misinformation...
Sacred or Synthetic? Evaluating LLM Reliability and Abstention for Religious Questions
arXiv:2508.08287v1 Announce Type: new Abstract: Despite the increasing usage of Large Language Models (LLMs) in...
s3: The new RAG framework that trains search agents with minimal data
S3 decouples RAG search from generation, boosting efficiency and generalization for enterprise LLM applications with...
Rubrics as Rewards (RaR): A Reinforcement Learning Framework for Training Language Models with Structured, Multi-Criteria Evaluation Signals
Reinforcement Learning with Verifiable Rewards (RLVR) allows LLMs to perform complex reasoning on tasks with...
