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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 ↗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.
- GitHub · Repository created · First archived
init-co-jp/diff-tour ↗
Walk through a diff the way a senior engineer reads it. A read-only TUI that turns a git change into a guided tour.
- GitHub · Repository created · First archived
korexil/gpu-duet ↗
Local LLM + voice-cloning TTS sharing one 8 GB GPU, as a server for ESP32 voice boards. 本地 LLM + 声音克隆 TTS 共用一块 8 GB 显卡，给 ESP32 语音板子当服务端。怎么省显存、怎么轮流、怎么不断音，附完整实测。
- GitHub · Repository created · First archived
Q-shuang-dot/officeace2api ↗
Turn a model gateway into a standard OpenAI-compatible API with a built-in web console. Zero deps (Node.js built-ins only). 把华为云果办 OfficeAce 模型网关反代成标准 OpenAI 兼容 API，自带中文控制台。
- Hacker News · Posted on Hacker News · First archived
Language models play chess, everything is recorded ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Ask HN: Are LLMs Solving Math? ↗
Are LLM agents solving all known math problems from low to high complexity consistently now or are LLMs "only" synthesizing solutions for ripe problems given humanities current math knowledge?
- OpenAlex · Published · First archived
SF-SRGAN: Shift-Free Transformer GAN with High-Frequency Enhancement for Image Super-Resolution ↗
Image super-resolution refers to the process of recovering high-resolution images from low-resolution inputs. However, existing methods face three critical challenges: GAN-based approaches suffer from training instability and artifacts; shifted-window Transformers have issues of computational cost and fixed receptive fields; and high-frequency detail modeling along with multi-source feature fusion remains insufficient. To address these issues, this paper proposes SF-SRGAN, a high-frequency enhanced shift-free Transformer generative adversarial network. The generator introduces a shift-free var…
- OpenAlex · Published · First archived
A Transformer Network for Settlement Generalization Integrating Raster Maps and Remote Sensing Images ↗
To address the challenges of reliance on manual expertise and insufficient automation and intelligence in settlement generalization during scale transformation, this paper proposes a multi-scale settlement generalization model (DSG-Trans) based on the fusion of dual-source data: raster maps and remote sensing images. Leveraging the cartographic correspondence between remote sensing image resolution and map scale, this model integrates source-scale maps with specific low-resolution remote sensing imagery to automatically generate target-scale raster maps that adhere to cartographic specificatio…
- OpenAlex · Published · First archived
VOICE-AE: automated CTCAE scoring from ambient clinical audio using speech recognition and large language models ↗
Abstract Treatment-related adverse event documentation is labor-intensive and subject to inter-observer variability. We developed and evaluated VOICE-AE, a multi-stage pipeline integrating automatic speech recognition, speaker diarization and large language models (LLMs) for automated extraction and grading of Common Terminology Criteria for Adverse Events (CTCAE) toxicities from clinician-patient audio recordings. Encounters of prostate cancer patients undergoing radiotherapy were recorded and processed through VOICE-AE. Six blinded human raters independently graded 10 genitourinary/gastroint…
- OpenAlex · Published · First archived
REW-DETR: A Lightweight Real-Time Detection Transformer for Bridge Surface Defect Detection ↗
Timely detection of bridge surface defects is important for structural safety assessment and inspection efficiency. To address defect scale variation, complex background interference, and the high computational cost of RT-DETR-R50, this study proposes REW-DETR, a lightweight bridge surface defect detector. REW-DETR adopts a coordinated lightweight design integrating efficient feature extraction, multi-level channel recalibration, and localization optimization. RepNCSPELAN4–ADown is employed to reconstruct the backbone and fusion stages, ECA is embedded at the P3–P5 feature levels to enhance ch…
- OpenAlex · Published · First archived
Knowledge generation and evaluation for construction quality assessment using retrieval-augmented large language models ↗
To address the problems of delayed knowledge updating, inefficient information acquisition, and difficulty in cross-project knowledge reuse in civil engineering construction quality assessment, this paper proposes a retrieval-augmented generation (RAG)-based methodology for injecting domain knowledge into large language models (LLMs). Multi-source knowledge, including national standards, journal articles, textbooks, and engineering reports, was systematically collected, cleaned, semantically segmented, and encoded using the bge-large-zh-v1.5 model to build a Milvus vector database. A general-p…
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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