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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 ↗460 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
Representing Search State to a Large Language Model: A Structured Telemetry Interface for Runtime Control of Adaptive Large Neighbourhood Search ↗
Adaptive large neighbourhood search is steered by high-level control decisions, yet its standard adaptation reacts to a narrow reward signal that conveys little about the state of the search. Recent work has strengthened this control with machine-learning and reinforcement-learning policies, but these generally require task-specific training. This paper proposes a framework in which a large language model acts as a bounded, training-free runtime supervisor of the search. The central contribution is a structured telemetry interface that compresses the evolving search into a compact, reproducibl…
- OpenAlex · Published · First archived
ASAS-NANP SYMPOSIUM: MATHEMATICAL MODELING IN ANIMAL NUTRITION: The Evolution of Large Language Models and Their Impact on Animal Sciences ↗
Abstract The rapid rise of large language models (LLM) is reshaping the scientific landscape, transitioning from early statistical language models to advanced transformer-based architectures capable of synthesizing knowledge across disciplines. While their predictive capacity and scalability have opened new avenues in data analysis, hypothesis generation, and decision support, concerns remain regarding bias, hallucination, reproducibility, and ethical governance. In animal sciences, LLM are gradually applied to challenges in nutrition modeling, animal health, genetic selection, and sustainabil…
- OpenAlex · Published · First archived
Optimal Design of the Microwave Oven Magnetic Shunt Transformer Using Physics-Based Equivalent Circuit Model and GNN-Guided NSGA-III Method ↗
Magnetic shunt transformers (MSTs) used in microwave ovens are designed with deliberately high leakage inductance for current limiting and voltage regulation. This requirement couples the core dimensions, winding parameters, shunt geometry, material cost, and power losses. This paper presents an optimal design strategy in which every candidate is evaluated by a physics-based equivalent circuit model and a graph neural network (GNN)-guided non-dominated sorting genetic algorithm III (NSGA-III) optimizer. In the proposed framework, all candidate designs are evaluated for their electromagnetic pe…
- OpenAlex · Published · First archived
Ensemble transformer-based framework for predicting finger angles ↗
Abstract More than 50% of individuals with upper-limb amputation reject the use of prosthetic devices, primarily due to limitations in functionality, comfort, and intuitive control. Accurate estimation of finger joint angles is a key requirement for proportional prosthetic control, as it enables the generation of continuous and natural hand movements that more closely mimic biological hand function. However, real-time prediction of finger joint angles remains challenging because of the nonlinear relationship between electromyographic signals and joint motion, as well as the computational const…
- OpenAlex · Published · First archived
Automated WAF Rule Generation from Adversarial Prompt Pattern Mining for Perimeter-Level Protection of LLM Applications ↗
This work proposes an adversarial prompt pattern mining methodology for the automated generation of Web Application Firewall (WAF) detection rules for the perimeter-level inspection of requests to Large Language Model (LLM) applications. The proposed methodology extracts linguistic patterns from an adversarial prompt corpus using sequential n-gram analysis, TF–IDF weighting, normalized frequency, and Interest Factor (IF) metrics. The resulting patterns are prioritized through a configurable scoring function and automatically transformed into ModSecurity-compatible rules capable of inspecting H…
- OpenAlex · Published · First archived
LLMs can assist with proposal selection at large user facilities ↗
Abstract We explore how large language models (LLMs) can enhance the proposal selection process at large user facilities, offering a scalable, consistent, and cost-effective alternative to traditional human review. Proposal selection depends on assessing the relative strength among submitted proposals; however, traditional human scoring often suffers from weak inter-proposal correlations and is subject to reviewer bias and inconsistency. A pairwise preference-based approach is logically superior, providing a more rigorous and internally consistent basis for ranking, but its quadratic workload…
- OpenAlex · Published · First archived
MergeRepair: An Exploratory Study on Merging Task-Specific Adapters in Code LLMs for Automated Program Repair ↗
Abstract Large Language Models (LLMs) have shown high capabilities in several software development-related tasks such as program repair, documentation, code refactoring, debugging, and testing. However, training these models requires massive amount of data and significant computational resources. Adapters are specialized, small modules designed for parameter efficient fine-tuning of LLMs for specific tasks, domains, or applications without requiring extensive retraining of the entire model. These adapters offer a more efficient way to customize LLMs for particular needs, leveraging the pre-exi…
- GitHub · Repository created · First archived
home-operations/kritika ↗
Repository-aware AI pull request reviewer for GitHub
- Hacker News · Posted on Hacker News · First archived
The model observes, a table decides: keeping an LLM out of pet triage ↗
Hacker News discussion.
- GitHub · Repository created · First archived
suvamneog/jobradar ↗
Watches company job boards, scores openings against your resume, and emails you when something worth applying to shows up.
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.
See the collection and counting methodology ↗ · Read the weekly synthesis ↗
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These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.