Knowledge catalogue
I developed https://lora-hunt.info/ for finding LoRA/PEFT adapters that might work with local LLM setups. The site collects public model metadata from Hugging Face and tries to make base-model compati
arXiv:2502.14254v3 Announce Type: replace-cross Abstract: Recent advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs) have made them powerful tools in embodied navigation, en
arXiv:2609.18084v1 Announce Type: cross Abstract: Fine-tuning a Vision-Language-Action (VLA) model for a new deployment environment is expensive, yet most methods apply uniform-capacity adapters to ev
arXiv:2408.07702v2 Announce Type: cross Abstract: Schema linking is a crucial step in Text-to-SQL pipelines. Its goal is to retrieve the relevant tables and columns of a target database for a user's q
arXiv:2609.17884v1 Announce Type: cross Abstract: As unmanned aerial vehicles (UAVs) become increasingly prevalent in consumer and defense settings, classifying them reliably from limited, modality-sp
arXiv:2604.04502v2 Announce Type: replace Abstract: Video generation models can produce coherent vi- sual sequences depicting object motion and interactions. We in- vestigate how frontier video genera
arXiv:2609.18286v1 Announce Type: new Abstract: Chess has long served as a model domain for studying search, expertise, decision-making, and artificial intelligence. The emergence of large language mo
arXiv:2509.09710v3 Announce Type: replace-cross Abstract: This study introduces a Large Language Model (LLM) scheme for generating key attributes of travel diaries in agent-based transportation models
arXiv:2609.17101v1 Announce Type: new Abstract: The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e.,
arXiv:2609.16500v1 Announce Type: new Abstract: Hidden Semi-Markov Models (HSMMs) are fundamental probabilistic models widely adopted across diverse domains, from computational biology to finance and
arXiv:2606.18960v3 Announce Type: replace Abstract: Action-conditioned world models have emerged as a promising paradigm for robot learning, offering a scalable alternative to costly real-world experi
arXiv:2609.17524v1 Announce Type: new Abstract: World-action models (WAMs) jointly model future observations and actions, typically predicting the future as RGB images. Other visual modalities such as
arXiv:2609.14819v1 Announce Type: cross Abstract: Large language models (LLMs) have a growing range of applications in medicine, and their evaluation is critical for ensuring they provide benefit and
arXiv:2404.03028v4 Announce Type: replace Abstract: Modern language models (LMs) can learn to perform new tasks in different ways: in instruction following, the target task is described explicitly in
arXiv:2609.15973v1 Announce Type: new Abstract: Foundation models have progressed from learning and reasoning over existing knowledge, to increasingly learning through action, tool use, and outcome fe
arXiv:2609.15089v1 Announce Type: new Abstract: Empathetic response generation in spoken dialogue systems requires both accurate emotion perception and appropriate emotion regulation. Grounded in psyc
arXiv:2609.13520v1 Announce Type: new Abstract: While Large Language Models have improved rapidly, many fundamental questions remain about how to evaluate the knowledge and reasoning abilities they ac
arXiv:2609.13534v1 Announce Type: new Abstract: We identify extbf{Harmfulness Propagation Dynamics (HPD)}: for harmful prompts, the projection of the last-token hidden state onto a learned harm direct
arXiv:2609.13195v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have recently shown strong capabilities in speech understanding and question answering (QA), but they also inherit
arXiv:2609.13514v1 Announce Type: new Abstract: Ensuring the reliability of black-box machine learning models in safety-critical space missions remains a significant challenge, particularly when groun
arXiv:2404.07729v2 Announce Type: replace-cross Abstract: Continual learning (CL) evaluates adaptability in learning solutions to retain knowledge. Our research addresses the challenge of catastrophic
arXiv:2609.13231v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models demonstrate strong generalization in robotic manipulation and navigation, but existing fine-tuning methods provide
Alix Coutures / The Information: Some developers are using the Claude Code harness to access cheaper non-Anthropic models, such as OpenAI's GPT-5.6 Sol, via proxies and services like OpenRouter — Bori
arXiv:2609.14258v1 Announce Type: new Abstract: Vision-language models (VLMs) remain vulnerable to jailbreaks that distribute harmful intent across text and images, making unimodal safety mechanisms i
arXiv:2609.15205v1 Announce Type: cross Abstract: Table extraction from texts is an important task for information systems, and recent approaches that prompt large language models (LLMs) with instruct
arXiv:2602.00165v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is a practical way to reduce the memory footprint of large language models, but low-bit quantization is sensitive t
arXiv:2609.12316v1 Announce Type: new Abstract: Collecting high-quality robot data remains a fundamental challenge for training robot foundation models. Task and motion planning (TAMP) offers a scalab
arXiv:2506.13061v4 Announce Type: replace Abstract: Diffusion probabilistic models generate samples by learning to reverse a noise-injection process that transforms data into noise. A key development
arXiv:2504.19023v2 Announce Type: replace-cross Abstract: Semantic reasoning aims to infer new knowledge from existing knowledge, with OWL ontologies serving as a standardized framework for organizing
Tested on Laptop with RTX 5060 8gb vram and 16gb ram Claude code - autocompact = false Ollama - Flash attention = 1, kv cache = q8_0 Gemma4 12B 64K - https://ollama.com/SetneufPT/Gemma4-12B-IT-QAT_Q4_
arXiv:2609.11135v1 Announce Type: new Abstract: Short-term photovoltaic (PV) power and global horizontal irradiance (GHI) forecasts are essential for effective dispatch, reserve scheduling, and grid o
arXiv:2606.21844v2 Announce Type: replace Abstract: As AI systems integrate into online spaces, differentiating them from humans in conversations is increasingly important. We present Inverse Turing B
arXiv:2609.10879v1 Announce Type: new Abstract: Recent work has identified incremental learning in shallow networks trained on single-index and multi-index models. However, existing analyses often rel
arXiv:2609.11163v1 Announce Type: cross Abstract: Structured pruning of large language models (LLMs) offers hardware-efficient compression, yet existing methods require calibration data, gradient comp
Tiffany Hsu / New York Times: MIT launches the LLM Election Observatory, a dashboard tracking how nearly a dozen AI models tailor responses to political queries during the 2026 US midterms — Artificia
arXiv:2609.09905v1 Announce Type: cross Abstract: Preference alignment for flow and diffusion models now spans online reinforcement learning and offline preference optimization, but the relation betwe
Tamara Djurickovic / Tech.eu: Paris-based Arlequin AI, which is developing proprietary models based on topological neural networks, raised a €28M Series A co-led by redalpine and OTB — Arlequin AI has
arXiv:2609.10226v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in reasoning and code generation, raising the prospect that they could assist in
arXiv:2609.09852v1 Announce Type: new Abstract: The advance of multimodal large language models (MLLMs) has fundamentally reshaped the paradigm of human-computer interaction, especially speech interac
arXiv:2609.10153v1 Announce Type: new Abstract: Arabic morphology remains challenging for large language models, since fluent generation does not guarantee accurate morphosyntactic control. Existing A
OpenAI now supports generating fully editable financial models, research notes, and pitchbooks directly in a firm’s existing Microsoft Office templates (Excel, Word, PowerPoint). Documents are created
arXiv:2609.05461v1 Announce Type: cross Abstract: Reward-free latent world models plan by scoring candidate actions with distances in a frozen latent space: an action is preferred if its predicted fut
arXiv:2609.07943v1 Announce Type: cross Abstract: There is significant uncertainty about whether abstractions like beliefs or desires usefully describe the behavior of large language models (LLMs). In
arXiv:2609.08220v1 Announce Type: new Abstract: Large language models (LLMs) have recently emerged as a promising tool for automating robot design from high-level specifications, yet they remain ineff
arXiv:2504.15928v3 Announce Type: replace Abstract: Artificial intelligence (AI) shows remarkable potential in medical imaging diagnostics, yet most current models require retraining when applied acro
arXiv:2609.07753v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) is an important modality in a wide range of imaging applications due to its versatile, long range and near all weather op
arXiv:2509.19994v3 Announce Type: replace Abstract: Multimodal pre-trained models (e.g., ImageBind), which align distinct data modalities into a shared embedding space, have shown remarkable success a
arXiv:2609.08130v1 Announce Type: new Abstract: Driver alerting from dashcam video requires sequential decision-making under partial observability: a system must decide not only whether a scene is ris
arXiv:2609.06967v1 Announce Type: new Abstract: Ensuring effective transfer learning for vision-language models without compromising their generalization performance is crucial. However, many existing
arXiv:2609.08412v1 Announce Type: new Abstract: Machine-learning weather models (MLWMs) now match or outperform operational numerical weather prediction (NWP) at global medium-range forecasting, at fa
arXiv:2609.09143v1 Announce Type: new Abstract: Image tokenizers define the ``visual language'' of unified multimodal models, yet are commonly studied through isolated metrics or generation-/understan
arXiv:2609.08367v1 Announce Type: new Abstract: Test-time adaptation (TTA) has emerged as a prominent strategy for adapting vision-language models to distribution shifts during inference. We conduct a
arXiv:2609.04428v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to annotate cultural texts at scales that are impractical for human coders. However, before their out
arXiv:2609.05189v1 Announce Type: new Abstract: Assessing the impacts of social policy changes is a widely acknowledged challenge for policymakers. Econometric methods can be unreliable when extrapola
// From Language Models to World-Acting Systems // A critical review of agentic AI, and a framework that is genuinely useful for deciding how much authority to hand an agent. Here is how it works. The
arXiv:2603.25685v2 Announce Type: replace-cross Abstract: Action-conditioned robot world models generate future video frames of the manipulated scene given a robot action sequence, offering a promisin
arXiv:2609.04714v1 Announce Type: cross Abstract: Striking a balance between helpfulness and safety remains a fundamental challenge in aligning large language models. To achieve this balance, models s
arXiv:2609.04823v1 Announce Type: cross Abstract: Although automatic text simplification (ATS) is critical for accessibility, its progress has not matched the rapid evolution of broader natural langua
arXiv:2609.04707v1 Announce Type: cross Abstract: Wireless foundation models (WFMs) have emerged as a promising approach for learning reusable representations from large-scale wireless data and adapti
I got a lot of ads for meshy recently and went to try it with hilariously bad results. It apparently can't do anything but decorative figurines. I wanted a body shell for an rc car and it just couldn'