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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 ↗455 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
Application of Retrieval-Augmented Generation Large Language Models in Stomatology: A Scoping Review ↗
Large language models (LLMs) have been gradually applied to tasks such as specialized question answering, educational assistance, clinical decision support, and knowledge integration in stomatology. However, general-purpose LLMs still suffer from critical limitations, including outdated knowledge, hallucinatory generation, untraceable information sources, and inadequate clinical adaptability. Retrieval-augmented generation (RAG) offers a core solution for improving the accuracy, interpretability, and evidential traceability of model outputs by integrating external authoritative knowledge sourc…
- Europe PMC · Published · First archived
AntiCapt: Fine-Tuned Nucleotide Language Models for Predicting and Designing Anticancer Aptamers ↗
Over the past decade, aptamers have emerged as promising therapeutics, with cancer therapeutics as a major research area. Existing computational methods, however, either predict aptamer-target pairs or design aptamers against a specific target. In this study, we present AntiCapt, a computational method for identifying single-stranded DNA (ssDNA) anticancer aptamers (ACAs) using sequence descriptors and fine-tuned nucleotide language models. The main dataset comprises 1,021 experimentally validated ACAs and an equal number of non-aptamer sequences. Comparative analysis revealed distinct pattern
- Europe PMC · Published · First archived
Bacterial Cheminformatics: Large Language Models and Challenges in Bacterial Chemspace ↗
The escalating global crisis of antimicrobial resistance (AMR), often characterized as a "silent pandemic," necessitates a paradigm shift in antibiotic discovery. Traditional cheminformatics pipelines, reliant on hand-crafted molecular descriptors and low-throughput screening, are increasingly insufficient to address the evolving threats of multidrug-resistant pathogens. This Opinion article explores the transformative integration of Large Language Models (LLMs) and foundational Transformer architectures into bacterial cheminformatics. We argue that the field is transitioning from simple discr
- GitHub · Repository created · First archived
cobanov/PS5LM ↗
llama.cpp on a jailbroken PS5: run any GGUF model natively on the console, starting with Qwen 3.8
- Hacker News · Posted on Hacker News · First archived
Kcc, a C compiler built solo with an LLM on $100/month boot Linux kernel ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Scrubbed – fast native web-data cleaning for LLM training ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Ask HN: Organize and Cleanup iCloud Photos Using LLMs or GrokBot and Muse ↗
I have accumulated gigabytes of smartphone photos over the past decade that i have not been able to properly manage or cleanup systematically. Has anyone been successful at using AI and a multitude of agentic tools to do things like * identify photos as candidates for deletion based on them being blurry or poorly composed or being duplicates * cluster photos as being part of a particular trip or particular iterinary based on their geographical an…
- arXiv · Published · First archived
TACO: Ternary Absolute-max Column-wise One-sparse Optimizer for LLM Fine-Tuning ↗
Full-parameter fine-tuning of large language models (LLMs) incurs substantial optimizer state memory overhead, limiting the model sizes that fit on modern GPUs. Existing approaches either compress optimizer state, abandon first-order gradients, or change the update geometry while retaining dense state. The recently introduced Muon optimizer reduces optimizer memory through matrix-valued updates. Still, its geometry differs from AdamW and can lead to performance degradation when fine-tuning AdamW-pretrained models. To reduce optimizer memory without sacrificing accuracy or computational efficie…
- arXiv · Published · First archived
Hierarchical Continuous Diffusion Language Models ↗
Discrete diffusion language models offer a compelling alternative to autoregressive generation for tasks demanding bidirectional reasoning and global constraint satisfaction. Yet they share a structural bottleneck: when decoding in parallel, each token is sampled independently from its marginal, severing the statistical dependencies among the tokens decoded together. Continuous diffusion language models avoid this by denoising a shared continuous state, but their denoiser sees only that state, so nothing ties it to a valid token configuration until it is finally decoded. To address this, we pr…
- arXiv · Published · First archived
The Missing Primitive: Diagnosing and Repairing Mathematical Reasoning in Large Language Models ↗
While Large Language Models (LLMs) have demonstrated striking capabilities on frontier mathematical problems, it remains unclear whether they possess the structural mathematical understanding underlying their solutions. In this paper, we take a first step toward systematically studying mathematical understanding in LLMs, from diagnosing its distinct capabilities to leveraging these findings to improve post-training. First, we introduce the notion of Mathematical Primitive to probe structural mathematical understanding and propose \hlei{}, a novel benchmark that evaluates mathematical reasoning…
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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