Large language model (LLM) news — GPT-4, Claude, Gemini, Llama, Mistral and the latest research on training, fine-tuning, RLHF, and deployment of LLMs.
Researchers introduced DynaSteer, a dynamic representation editing framework that steers large language model reasoning trajectories toward truth by leveraging geometric insights into truth encoding and entropy-based int…
Researchers introduced VirtueMap, a framework that profiles large language models (LLMs) based on Aristotelian virtues by ranking responses to ethical dilemmas. Testing on nine LLM families revealed high rank consistency…
Researchers introduced BV-Blend, a critic-free reinforcement learning framework that stabilizes advantage estimation for aligning large language models by blending prompt-local on-policy statistics with semantic-cluster-…
Researchers used evolutionary game theory to model when a harm-minimizing AI agent can outcompete an approval-seeking (RLHF) agent in a competitive market. They found adoption depends on specific properties of community …
Researchers introduced Agentic Abstention, a framework for LLM agents to decide when to stop acting under uncertainty, and found that many agents fail to abstain or do so too late. Testing 13 LLM agents and 2 scaffolds o…
Researchers argue that applying content-safety methods like refusal training to LLM agents is a category error, as agentic harm lies in the relation between exercised authority and granted authority, not in model outputs…
Researchers developed a self-supervised theorem-discovery algorithm that starts from axioms and inference rules alone, autonomously building a library of useful theorems. The agent discovered tens of thousands of theorem…
Researchers at arXiv propose a mechanistic interpretability method to steer the OCEAN personality traits of large language models by intervening on latent features via sparse autoencoders and contrastive activation analy…
Researchers introduced HyphaeDB, an agent-native memory infrastructure that repurposes HNSW graph topology from vector databases into a communication fabric for multi-agent AI systems, enabling knowledge propagation and …
Researchers used frozen medical large language model (LLM) representations to predict primary ICD categories from both clinical narratives and structured EHR data, achieving 87.69% strict accuracy on MIMIC-IV. The multim…
A study evaluating AI tools on real clinical queries from physicians found that a specialized clinical tool (OpenEvidence) outperformed frontier general-purpose models (Claude Opus 4.8, Gemini 3.1 Pro, GPT-5.5) across al…
A developer proposes decoupling AI features from specific model names by defining service objectives that specify task, quality, latency, and cost constraints. This approach allows an intelligence layer to select the bes…
Fastllm, a C++ LLM inference library, now supports running DeepSeek-V4 and the full DeepSeek R1 671B model on a single GPU with just 10GB VRAM. The library is compatible with Nvidia, AMD, and domestic GPUs, and supports …
A new guide shows developers how to build a private AI coding assistant using Ollama, Continue, and MCP, with benchmarks from real-world workstations.
Researchers from Tsinghua University and Meituan introduced U-Mind, a unified framework for real-time multimodal interaction that enables a large language model to reason across text, speech, and motion. The model, accep…
A test of five leading AI systems—Claude, Gemini, GPT-5, Mistral, and Cohere—using 116 identical ethics and safety prompts found that the systems disagreed with each other 34% to 66% of the time, and individual systems c…
Researchers from Tsinghua University and Z.ai have proposed IndexCache, a method to reduce the computational cost of DeepSeek Sparse Attention (DSA) in GLM-5.2. IndexCache exploits the observation that adjacent layers in…
A developer intentionally broke hydration in a Next.js app to understand how it works internally. By causing mismatches with new Date(), typeof window, and Math.random(), they discovered that hydration relies on exact DO…
Anthropic's Claude Code agent system offers four extension points—skills, hooks, custom slash commands, and MCP servers—that developers can use to control costs and behavior. A hands-on test of skills and hooks shows tha…
Large language models face speed bottlenecks due to KV cache, batching, and quantization challenges, and modern AI systems employ techniques to overcome these issues.