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Earlier sources: Language models
Language models learn patterns in text and other representations to predict or generate sequences. Follow model releases, training methods, reasoning, evaluation, and deployment research; a benchmark result is specific to its test conditions.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗450 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
Hybrid Vulnerability Discovery in the Wild: Automated Screening, Fine-Tuned LLMs, and Four Published CVEs ↗
Automated security scanners produce many alerts, but disclosure requires evidence of attacker control, reachability, impact, and reproducibility. We present an evidence-gated workflow that screens recently updated Python AI/ML and data-science packages then uses two separately fine-tuned open-weight agents to distinguish vulnerability plausibility from CVE worthiness: the first tests attacker control and reachability, and the second assesses novelty and impact before human proof-of-concept validation and coordinated disclosure. In a targeted campaign covering 400 packages, screening yielded 12…
- OpenAlex · Published · First archived
Adaptive Rogers’ Ratio-Based Transformer Fault Diagnosis: A New Hybrid Fungal Growth Optimizer with Teaching-Learing-Based Optimization (FGO–TLBO) Metaheuristic for Explainable Intelligent Optimization Framework ↗
Accurate identification of transformer insulation faults is essential for reliable power-system operation, and dissolved gas analysis (DGA) remains an important diagnostic tool. However, conventional Rogers’ Ratio interpretation relies on fixed decision boundaries that may not represent overlapping gas patterns and measurement variability. This study proposes an explainable Hybrid FGO–TLBO framework that adaptively calibrates four Rogers’ Ratio decision boundaries while preserving the original rule-based diagnostic logic. The study uses 500 real DGA records representing six classes: Normal, Pa…
- OpenAlex · Published · First archived
Energy management optimization algorithm for data center microgrids based on solid-state transformers ↗
The proliferation of hyperscale data centers, together with tightening carbon-neutrality targets, exposes the limits of the line-frequency transformer (LFT) that still dominates data-center power distribution and motivates a fresh look at the conversion and dispatch layer. This paper develops an energy management framework for a data-center microgrid whose grid interface is a three-stage solid-state transformer (SST), so that renewable, storage, and IT loads sit on independently regulated AC and DC ports rather than behind a passive iron core. A multi-objective mixed-integer nonlinear program…
- OpenAlex · Published · First archived
Quantum Hall transformer in a quantum point contact over the full range of transmission ↗
A recent experiment [Cohen et al., Science 382, 542 (2023)] observed a robustly quantized $e^2/2h$ conductance in a quantum point contact between fractional quantum Hall edges (a quantum Hall transformer), which then vanishes at low temperature. While this behavior can be described by a boundary sine gordon (BSG) model derived from electron tunneling, the microscopic motivation for such strong tunneling is unclear. We use an alternative model based on sliding charge density waves and a density inhomogeneity to clarify the BSG description and calculate the conductance over the full range of tra…
- GitHub · Repository created · First archived
BaruqueRodrigues/llm-legislativo ↗
Corpus legislativo brasileiro em larga escala e modelo Transformer causal treinado do zero em PyTorch puro.
- Hacker News · Posted on Hacker News · First archived
Show HN: Enki LLM A pure rust (even kernels) with live GPU/CPU brain migration ↗
Hacker News discussion.
- GitHub · Repository created · First archived
anisayari/sparky ↗
🔒 Your private AI assistant, 100% local on Windows: chat, vision, documents (RAG), web search, images, videos with sound, voice, code projects, MCP tools — one-line install, models picked for your PC.
- Hacker News · Posted on Hacker News · First archived
Show HN: Commit-Aware Router, route LLM traffic around your AI/cloud commitments ↗
LLM routers can optimize for different factors like price, latency, quality, etc. Enterprises tend to have prepaid AI credits, minimum-spend agreements, cloud commitments, or commercial ceilings across OpenAI, Anthropic, AWS, Azure, and other providers. We’ll call these “AI commits”. This project is designed to consider the state of an enterprises’ current AI commits and use it to inform LLM routing decisions alongside other common variables (pri…
- arXiv · Published · First archived
PixelMoE: Scaling Pixel-Space Diffusion with LLM-Style Mixture-of-Experts ↗
Pixel-space diffusion models provide an appealing alternative to latent-space diffusion models by directly modeling raw images without relying on a learned tokenizer. However, scaling pixel-space models has predominantly followed dense strategies, tightly coupling model capacity with active computation. In this work, we show that standard LLM-style Mixture-of-Experts (MoE) architectures can be effectively transferred to pixel-space diffusion. Building on this finding, we introduce PixelMoE, a pixel-space generative framework that sparsely scales model capacity with standard LLM-style MoE, with…
- arXiv · Published · First archived
RepProbe: Can Video Language Models Count Repeated Actions? A Diagnostic Benchmark ↗
Repetition counting requires identifying and enumerating action cycles over time. While state-of-the-art video language models describe actions fluently, they fail to reliably count how many times an action repeats. To investigate this limitation, we introduce RepProbe, a benchmark of 42K real and synthetic video clips containing exactly k in [1, 20] complete repetitions, with controls for clip position, temporal coverage, and duration. These controls allow us to study the counting failure directly and locate where in the model it arises. Counting accuracy collapses at high counts across the v…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Language models
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.