Noticias
Static vs. Dynamic vs. Continuous Batching in LLM Inference
In this article, you will learn how static, dynamic, and continuous batching work in LLM...
Static vs. Dynamic vs. Continuous Batching in LLM Inference
In this article, you will learn how static, dynamic, and continuous batching work in LLM...
Stateful vs. Stateless Agent Design: Tradeoffs for Scalable Agentic Systems
In this article, you will learn how an agent’s approach to managing state — stateless...
Start Making Sense(s): A Developmental Probe of Attention Specialization Using Lexical Ambiguity
arXiv:2511.21974v1 Announce Type: new Abstract: Despite an in-principle understanding of self-attention matrix operations in Transformer...
STAR-Bench: Probing Deep Spatio-Temporal Reasoning as Audio 4D Intelligence
arXiv:2510.24693v2 Announce Type: replace-cross Abstract: Despite rapid progress in Multi-modal Large Language Models and Large...
Stanford Researchers Release Paper2Agent: Turning Research Papers Into AI Agents That Reproduce Results and Run on New Data
Computational papers ship code that readers must clone, install, configure and debug. That cost keeps...
Stanford Researchers Introduce TRACE: A Capability-Targeted Agentic Training System That Turns Recurrent Agent Failures Into Synthetic RL Environment
Agentic LLMs often fail the same way, again and again. A Stanford research team traced...
Stand Up for Research, Innovation, and Education
Right now, MIT alumni and friends are voicing their support for: America’s scientific and technological...
Stacked from One: Multi-Scale Self-Injection for Context Window Extension
arXiv:2603.04759v1 Announce Type: new Abstract: The limited context window of contemporary large language models (LLMs)...
Stable Signer: Hierarchical Sign Language Generative Model
arXiv:2512.04048v1 Announce Type: cross Abstract: Sign Language Production (SLP) is the process of converting the...
Stabilizing Knowledge, Promoting Reasoning: Dual-Token Constraints for RLVR
arXiv:2507.15778v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become an effective...
SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction
arXiv:2605.23440v4 Announce Type: replace Abstract: Joint Entity and Relation Extraction (JERE) is highly sensitive to...
