Model Detail
GPT-OSS-20B-Uncensored-HauhauCS-Aggressive
—GPT-OSS-20B-Uncensored-HauhauCS-Aggressive is an AI model with 20B parameters released by HauhauCS. It has accumulated 6K downloads on Hugging Face since publication.
GPT-OSS-20B-Uncensored-HauhauCS-Aggressive ships with 20B parameters.
GPT-OSS-20B-Uncensored-HauhauCS-Aggressive is best fit for general-purpose AI workloads. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
Language-Based Digital Twins for Elderly Cognitive Assistance
arXiv:2606.27334v1 Announce Type: new Abstract: Digital twins have emerged as a promising paradigm for personalized healthcare, enabling modeling of individual behavior and health trajectories. In cognitive health, early detection of Mild Cognitive Impairment (MCI) remains challenging, where languag
Datadog veterans launch AI coding startup Niteshift on a bet against Big AI lock-in
AI coding agent startup Niteshift has raised a $7 million seed round from a who's who of angels. It's betting companies will want power over, not lock-in with model makers.
Refining and Reusing Annotation Guidelines for LLM Annotation
arXiv:2605.20809v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable performance on zero-shot annotation tasks, they often struggle with the specialized conventions of gold-standard benchmarks. We propose the systematic reuse and refinement of annotation guidelin
The Single-File Test: A Longitudinal Public-Interface Evaluation of First-Output LLM Web Generation with Social Reach Tracking
arXiv:2605.06707v1 Announce Type: cross Abstract: This paper presents an eight-week observational comparison of 68 single-file HTML generations collected across 17 public experiments in the "HTML AI Battle" project between December 10, 2025 and February 4, 2026. Four reasoning model families, GPT, G
NRGPT: An Energy-based Alternative for GPT
arXiv:2512.16762v3 Announce Type: replace Abstract: Generative Pre-trained Transformer (GPT) architectures are the most popular design for language modeling. Energy-based modeling is a different paradigm that views inference as a dynamical process operating on an energy landscape. We propose a minim
Surface Sensitivity in Lean 4 Autoformalization
arXiv:2604.23135v1 Announce Type: new Abstract: Natural-language variation poses a key challenge in Lean autoformalization: semantically equivalent paraphrases of the same theorem statements can induce divergent formal outputs, yet it remains unclear whether this variation reflects semantic disagree
