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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 ↗437 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
Physically Constrained Temporal Fusion Transformer with LLM-Assisted Hyperparameter Optimization for Multi-Scenario Energy Time Series Forecasting ↗
Accurate forecasting of battery state of health (SOH), wind power, and photovoltaic (PV) power is challenged by non-stationarity, multiscale dependencies, and physically implausible outputs. This study proposes a physically constrained Temporal Fusion Transformer (PC-TFT) that coordinates enhanced temporal representation, physical regularization, and LLM-assisted Bayesian optimization. Mogrifier-LSTM and a feature-enhanced attention module capture transient fluctuations and long-range dependencies, while spectral normalization stabilizes training under physical constraints. Scenario-specific d…
- OpenAlex · Published · First archived
Transformer architecture incorporating discrete wavelet transform for fully automated baseline correction of near-fault ground-motion records ↗
Baseline correction of near-fault ground motions (NFGMs) is essential for characterizing permanent displacement and pulse-like features, but remains challenging because low-frequency noise must be removed without distorting physically meaningful components in integrated velocity and displacement histories. Conventional correction methods rely heavily on manually selected parameters or time windows, whereas deep-learning methods are limited by inadequate representation of noise–pulse interactions and synthetic datasets that often neglect pulse-like characteristics. This study proposes a fully a…
- OpenAlex · Published · First archived
RAG-ReAct empowered large language models for localized intelligent bridge operation and maintenance: a knowledge-driven agentic approach ↗
Bridges serve as critical transportation infrastructure hubs. The recent breakthroughs in large language models (LLMs) offer transformative potential for intelligent bridge operation and maintenance (O&M), but their direct application is hindered by domain-specific hallucination, black-box reasoning opacity, and passive response limitations. This manuscript proposes a knowledge-driven, edge-side bridge O&M agent based on LLMs, addressing those critical limitations of general-purpose LLMs in specialized structural health monitoring (SHM) domains. The methodology centers on three core technical…
- OpenAlex · Published · First archived
A deep hybrid feature extraction model based on MobileNet and vision transformer for acute lymphoblastic leukemia prediction ↗
Abstract Early and accurate identification of Acute Lymphoblastic Leukemia (ALL) from peripheral blood smear images can support microscopic screening, but reliable evaluation requires both discriminative feature learning and transparent reporting of the experimental protocol. This study presents MoViTHAFX-Net, a hybrid MobileNet–Vision Transformer (ViT) architecture with Hierarchical Attention Fusion (HAF) and Grad-CAM++ visualization for binary classification of ALL blasts and healthy hematogones (HEM) using the 10,661 labelled cell images in the training component of the C-NMC 2019 dataset.…
- OpenAlex · Published · First archived
DSFormer: An Enhanced Dual-Selective Fusion Transformer Framework for Hyperspectral Image Classification++ ↗
Hyperspectral image classification requires joint modeling of spectral signatures and spatial structure. In patch-based classification, each input patch is assigned the label of its center pixel, although neighboring pixels may belong to different land-cover classes. This setting motivates coordinating shallow spatial features, contextual refinement within the patch, and supervision of the resulting representation. We propose DSFormer++, an enhanced framework based on the original Dual Selective Fusion Transformer Network (DSFormer). Shallow Feature Compensation (SFC) combines shallow and patc…
- GitHub · Repository created · First archived
final-bench/ongrid ↗
ONGRID — Ontology-Native Graph · Retrieval · Inference · Decision. 3D knowledge graph + zero-token ZTC answer verification. by VIDRAFT.
- Hacker News · Posted on Hacker News · First archived
open-slopware – Alternatives to FOSS projects choosing to use LLMs/AI ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Kisoku 1.6B: LLM trained solo from scratch on a TPU grant, matches Llama 3.2 1B ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Improving 25 square packing upper bounds through evolutionary LLM program search ↗
Hacker News discussion.
- arXiv · Published · First archived
Can Language Models Play the Wikipedia Game? ↗
Language models increasingly support or automate information retrieval from document collections too large to index. This task is difficult when it requires specialist linguistic or scientific knowledge. We used the Wikipedia Game to test language models on an analogous information retrieval task. In the game, players must reach a target article using only article links. We compared sentence embedding models and LLMs across five Wikipedia languages and five academic-literature datasets. We construct very large local graphs of Wikipedia pages and of paper citations using OpenAlex and provide co…
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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