Knowledge catalogue
arXiv:2604.08885v1 Announce Type: new Abstract: Transformers have had a profound impact on the field of artificial intelligence, especially on large language models and their variants. However, as was
This r/StableDiffusion post likely discusses the community challenge of using OneTrainer — a locally-installed, GUI-based LoRA training tool — to train LoRAs specifically compatible with Z Image (Tong
@hwchase17 I think harness/managed agents is a way for Anthropic to keep its Moat. As models get mature, the need for cloud LLMs might reduce and local LLM models might increase (save cost) and thus t
arXiv:2604.06227v1 Announce Type: new Abstract: Accurate short-term forecasting of agricultural commodity prices is critical for food security planning and smallholder income stabilisation in developi
arXiv:2604.06207v1 Announce Type: cross Abstract: This paper investigates demonstration selection strategies for predicting a user's next point-of-interest (POI) using large language models (LLMs), ai
arXiv:2601.20524v2 Announce Type: replace Abstract: Zero-shot anomaly detection aims to detect and localise abnormal regions in the image without access to any in-domain training images. While recent
arXiv:2509.23435v2 Announce Type: replace-cross Abstract: The creation of high-quality multimodal datasets remains fundamental for advancing role-playing capabilities in large language models (LLMs).
arXiv:2604.07606v1 Announce Type: new Abstract: AI-driven sign language interpretation is limited by a lack of high-quality annotated data. New datasets including ASL STEM Wiki and FLEURS-ASL contain
arXiv:2601.03786v2 Announce Type: replace Abstract: Training data influence estimation methods quantify the contribution of training documents to a model's output, making them a promising source of in
arXiv:2401.00870v5 Announce Type: replace-cross Abstract: State-of-the-art large language models (LLMs) are typically deployed as online services, requiring users to transmit detailed prompts to cloud
arXiv:2604.07717v1 Announce Type: new Abstract: Human immunodeficiency virus (HIV)-related stigma is a critical psychosocial determinant of health for people living with HIV (PLWH), influencing mental
arXiv:2604.08284v1 Announce Type: new Abstract: Large language models store not only isolated facts but also rules that support reasoning across symbolic expressions, natural language explanations, an
arXiv:2604.06826v1 Announce Type: cross Abstract: Environmental, Social, and Governance (ESG) considerations are increasingly integral to assessing corporate performance, reputation, and long-term sus
arXiv:2512.09928v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have recently enabled robotic manipulation by grounding visual and linguistic cues into actions. However, most V
arXiv:2604.06356v1 Announce Type: cross Abstract: In-Context Learning (ICL) has been extensively studied in text-only Language Models, but remains largely unexplored in the speech domain. Here, we inv
arXiv:2603.04165v3 Announce Type: replace-cross Abstract: Large-scale 2D foundation models exhibit strong transferable representations, yet extending them to 3D volumetric data typically requires retr
arXiv:2604.07779v1 Announce Type: new Abstract: Pathology foundation models (FMs) have become central to computational histopathology, offering strong transfer performance across a wide range of diagn
arXiv:2510.05921v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved remarkable success in a wide range of natural language processing tasks and can be adapted through prompt
arXiv:2510.07048v2 Announce Type: replace Abstract: Despite their remarkable natural language understanding capabilities, Large Language Models (LLMs) have been underutilized for retrieval tasks. We p
Some strong embeddings models have been released recently. Ours is still better. We benchmarked Embed 5 Fast against Google's EmbeddingGemma 2 across 163 datasets using RCP-nDCG@10. Embed 5 Fast leads
arXiv:2602.16653v4 Announce Type: replace Abstract: Skills are getting increasingly used in recent agentic frameworks, performing robustly with proprietary LLMs. Yet, their effectiveness for small and
arXiv:2610.21681v1 Announce Type: new Abstract: Data strategy plays a central role in training large language models (LLMs). It governs the selection, weighting, and scheduling of training data, there
arXiv:2610.20917v1 Announce Type: new Abstract: Occupancy predictors rely on large persistent banks of Gaussians or learned queries whose size is fixed by hand. Common pruning proxies, such as opacity
arXiv:2610.21300v1 Announce Type: new Abstract: To show that a medical device complies with regulation, experts judge whether documents and records meet each requirement and record the judgment for ot
arXiv:2610.21810v1 Announce Type: cross Abstract: Conditional memory expands language-model capacity through selective lookup, but the full embedding table must remain available for every possible inp
arXiv:2610.21125v1 Announce Type: new Abstract: Few-step generative models produce high-quality samples in one or a few evaluations. However, steering them toward desired properties remains difficult,
arXiv:2610.20687v1 Announce Type: new Abstract: Residual context is key to unlocking the speed-quality Pareto frontier of diffusion language models (DLMs) by carrying forward predictive distributions
arXiv:2610.20781v1 Announce Type: cross Abstract: Image-to-text (I2T) understanding and text-to-image (T2I) generation are dual tasks in unified multimodal models (UMMs). Reconstructive post-training
arXiv:2610.17827v1 Announce Type: new Abstract: Existing approaches to training and evaluating search agents focus heavily on final-answer quality, largely neglecting how generated answers map back to
arXiv:2510.08464v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models are a promising paradigm for field robotics, but their deployment is bottlenecked by strict edge SWaP-C co
arXiv:2608.28281v2 Announce Type: replace Abstract: Loop Engineering is emerging as a practice for organizing development work around coding agents. Instead of writing each prompt by hand, practitione
arXiv:2610.17059v1 Announce Type: new Abstract: Clinical decisions depend on anticipating how a patient's condition will evolve as treatment is adjusted and new evidence becomes available. Existing me
arXiv:2610.20503v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by drafting multiple tokens per step, yet feature-based drafters rely on target hidden featur
Artificial intelligence governance startup nFOX Lab today launched a platform for managing owned large language models and announced plans to open-source Blockhouse, a security sandbox designed to res
arXiv:2610.19517v1 Announce Type: cross Abstract: Vision-language-action (VLA) models connect visual perception and language understanding with robot control, providing a foundation for instruction-co
In October 2026, Victor M announced a performance boost for inspecting model tensors on the Hugging Face Hub, achieving up to a 20× speed increase. Sample results include DeepSeek‑V3.2 dropping from 9
arXiv:2610.19202v1 Announce Type: new Abstract: Rare but severe failures of large language models can become practically significant at deployment scale. Estimating their probabilities with direct Mon
arXiv:2610.16325v1 Announce Type: new Abstract: When a steering intervention changes a language model's behavior, which part of the intervention deserves the credit? We test this question for a target
arXiv:2610.17495v1 Announce Type: new Abstract: In humans, proprioception corresponds to the sense of self-movement or position, e.g. understanding the position of one's arm. This sense is often less
arXiv:2610.16835v1 Announce Type: cross Abstract: Model providers can support image protection, but open-weight deployment introduces practical constraints. We propose four requirements: protection ef
Learn how to deploy an available model from Amazon SageMaker JumpStart, run a lightweight and repeatable performance test using the SageMaker Python SDK, and delete the endpoint when testing is comple
arXiv:2610.17882v1 Announce Type: new Abstract: Flow-based image generators achieve strong semantic synthesis but still produce localized structural distortions, such as malformed hands and limbs. Exi
arXiv:2610.17503v1 Announce Type: new Abstract: Event logs are ubiquitous across real-world domains, including business processes, manufacturing workflows, healthcare, and many other operational syste
arXiv:2610.16744v1 Announce Type: new Abstract: Video large language models (Video LLMs) encode each frame into hundreds of visual tokens, making video inference expensive. Existing methods reduce thi
arXiv:2610.17706v1 Announce Type: new Abstract: Large vision-language models often exhibit object hallucination, generating claims that are not supported by the input image. To mitigate this issue, we
arXiv:2610.16558v1 Announce Type: cross Abstract: World models capture environment dynamics and support counterfactual reasoning for planning. In image-goal navigation, where the target often lies bey
arXiv:2610.14813v1 Announce Type: new Abstract: Dengue is a viral infection caused by the dengue virus (DENV) and a major public health concern in Bangladesh, where symptom overlap with other febrile
arXiv:2610.16666v1 Announce Type: new Abstract: Vision-language models (VLMs) like CLIP have shown great success in image tasks, however, applying CLIP to open-vocabulary video recognition poses chall
arXiv:2606.13209v2 Announce Type: replace Abstract: Reward models (RMs) are a key component of reinforcement learning from human feedback, enabling the alignment of large language models with human va
Robots That Predict the Future: Dyna-2, Million-Hour World Models, & the Bitter Lesson of Robotics @DynaRobotics’s @JasonMa2020 explains how world-action models predict the future to guide physical ro
On October 13 2026, researcher Ethan Mollick tweeted that observing Gemini 4’s behavior reveals how many other LLMs are likely distilled from Claude or GPT—and thus use a similar training pipeline—mak
Learn how to deploy decision models with llama.cpp on Amazon SageMaker AI. This technical how-to serves OpenAI-compatible chat completions with the AWS Deep Learning Container for llama.cpp, then exte
arXiv:2610.12538v1 Announce Type: new Abstract: Modern machine learning models are typically trained on data assumed to be representative of the predictive tasks the model will face in the future, but
I've been investigating some serious ChatGPT reliability issues over the past several days, and my latest tests revealed something particularly interesting: Both GPT-5.6 and GPT-6 showed problems unde
arXiv:2610.12870v1 Announce Type: cross Abstract: Practical ship design requires localized refinement and performance evaluation. This paper presents a reward-directed diffusion framework for localize
arXiv:2610.13834v1 Announce Type: new Abstract: Continuous diffusion language models (CDLMs) promise to bring the benefits of continuous flow modelling to language, including accelerated sampling and
arXiv:2606.16939v2 Announce Type: replace-cross Abstract: A prominent research direction in mechanistic interpretability is learning sparse circuits over LLM components to reveal how they jointly prod
arXiv:2610.12696v1 Announce Type: new Abstract: Vision-language-action models (VLAs) offer a promising route toward general-purpose robotics by transferring semantic knowledge from large-scale vision-
arXiv:2610.13654v1 Announce Type: new Abstract: Tabular foundation models (TFMs) are increasingly popular for their strong predictive performance. Many also provide posterior predictive distributions
arXiv:2610.12544v1 Announce Type: new Abstract: Masked diffusion models (MDMs) generate discrete data by iteratively unmasking multiple tokens in parallel using a learned mask predictor. Their output