Large language model (LLM) news — GPT-4, Claude, Gemini, Llama, Mistral and the latest research on training, fine-tuning, RLHF, and deployment of LLMs.
A developer connected ChatGPT to FORMLOVA's remote MCP server, enabling ChatGPT to create and operate forms directly via tool calls. The setup uses OAuth authentication and a remote MCP URL, allowing ChatGPT to generate …
The White House issued an export-control designation on Anthropic's Fable 5 and Mythos 5 models, barring any foreign national from using them, after Amazon shared a jailbreak demonstration with administration officials. …
A developer outlines a blueprint for building a natural language query interface for databases using LLMs. The system architecture includes schema retrieval via RAG, prompt assembly, SQL generation, validation, and safe …
GitHub's infrastructure buckled under a surge of AI-generated code, with commits on pace to hit 14 billion in 2026, up from 1 billion in 2025. The platform suffered 19 service-degrading incidents in April and May, and Mi…
XAI's Grok coding model is now natively integrated into the Warp terminal, allowing SuperGrok subscribers to use it without consuming Warp platform credits. The move adds Grok to Warp's existing AI model lineup including…
Researchers introduced disagreement-based cross-model routing for implicit video question answering, achieving a +1.43 AvgAcc improvement on the ImplicitQA benchmark by routing disputed questions from Gemini 3.1 Pro Prev…
Researchers introduced HorusEye, a framework using language as dynamic attention for emergency visual analysis, and benchmarked it on the RefCOCO-Degraded dataset. Testing multiple vision-language models, they found Gemi…
Researchers propose Style-CCL, a multi-stage curriculum continual learning framework for content-preserving style transfer using Diffusion Transformers. The method trains a dual-branch SC-DiT from semantic to texture sty…
Researchers introduced X-Tokenizer, a multimodal action tokenizer for vision-language-action pretraining that uses Semantic Residual Quantization and Masked Action Modeling to create a discrete action language capturing …
Researchers propose sub-semantic image segmentation, a new category that partitions images into stable appearance patterns described by language rather than naming whole objects. They introduce DETECTURE, a system that o…
Researchers at arXiv propose a behavioral measure of trust between AI agents based on costly verification in a cooperative survival game. Testing six frontier model snapshots, they found that larger models like Claude Op…
Researchers introduced PrologMCP, an open-source server that exposes Prolog as a stateful tool through the Model Context Protocol, enabling LLM agents to delegate deductive reasoning tasks to a symbolic solver. In evalua…
Researchers propose SERAF, a semantics-enhanced retrieval-augmented time series forecasting framework that retrieves both historical time series segments and their self-generated textual descriptions to improve predictio…
Researchers developed Metric Match, a subset selection method that estimates LLM judge reliability from limited human annotations. The method achieved a win-rate of 0.838 against random selection across 15 datasets, redu…
Researchers introduced an LLM-driven framework for retrieving remote sensing data from cloud-based geospatial catalogues using natural language queries. The system uses three agents—Guardrail, General-QA, and Recommender…
Researchers applied the Verifiable Growing Physical Transformer with Recursive Self-Improvement (VGPT-RSI) to produce formally verified partial progress on problems adjacent to the Riemann Hypothesis, including a finite …
Researchers introduced IRTS-ToolBench, a benchmark of 1,700 questions across 10 task types and 13 domains, to evaluate large language models and AI agents on irregular time series question answering. The benchmark addres…
Researchers propose CONCORD, an asynchronous sparse aggregation framework for device-cloud retrieval-augmented generation under document isolation, which improves throughput by up to 2.15x and reduces communication by ov…
Researchers propose CogGuard, a proactive-warning framework for edge intelligent services that uses LLMs for offline profile construction and SLMs for online score prediction. The framework reduces profile construction t…
Researchers propose Visual-Seeker, a multimodal deep search agent that actively reasons over visual details to perform multi-hop, cross-modal search. The agent achieves state-of-the-art results on five benchmarks, surpas…