model releases

arXiv:2610.00309v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in privacy-critical domains (e.g., healthcare, finance, and government), but their propensity t

arXiv:2610.01763v1 Announce Type: new Abstract: Activation sparsity speeds up large language model (LLM) inference by setting unimportant activations to zero so that the corresponding computations can

arXiv:2610.00895v1 Announce Type: cross Abstract: Foundation models remain vulnerable to spurious correlations and ``Clever Hans'' strategies. Explainable machine learning can find and remove such str

arXiv:2603.21152v4 Announce Type: replace-cross Abstract: Modern seismic networks resolve earthquake sequences in unprecedented detail, yet explaining how large earthquakes emerge from evolving fault

arXiv:2610.01887v1 Announce Type: cross Abstract: Dynamic resource assignment, the real-time allocation of task streams to heterogeneous processing nodes, is the backbone of modern computing infrastru

arXiv:2610.00835v1 Announce Type: new Abstract: Text-to-music generation models are trained on massive music collections, creating a growing need for data attribution methods that can quantify the con

https://huggingface.co/Wa1k3r/Qwen3.8-27b-CODER-4q_xs-24GB-262k-Optimalcardfit Qwen3.8-27B CODER — IQ4_XS imatrix · 24 GB card fit · ~262k context · MTP draft Quantized, Abliterated, and fitted by Lex

I have been building a somewhat unusual local inference machine around two Huawei Atlas 300I Duo cards. They are relatively inexpensive, passive, dual-accelerator PCIe cards with 96 GB of device memor

arXiv:2610.00953v1 Announce Type: cross Abstract: An answer candidate in a masked diffusion MLLM can stabilize while its rationale is still unfolding. We distinguish retrospective stabilization of the

arXiv:2610.00188v1 Announce Type: cross Abstract: Voxel-based volumetric mapping is fundamental to 3D reconstruction, yet fixed-resolution grids remain inherently inefficient - wasting memory in unifo

arXiv:2610.00341v1 Announce Type: cross Abstract: As Large Multimodal Models (LMMs) transition toward natively unified architectures, evaluating their safety in synergistic harmful image-text generati

arXiv:2610.01981v1 Announce Type: new Abstract: Universal approximation is a necessary qualitative property of learning architectures to benefit from scaling laws. While it is generically verified on

Last update for those who may be following: https://www.reddit.com/r/LocalLLaMA/comments/1wv5h8x/update_2_post_training_yandexaliceai80ba3b/ I screwed up guys 😂 Turns out my loss curve during my last

This is 6 bc-250 ex mining boards with 5 in the asrock 4u12g case they came in. After a lot of testing my current preferred setup is 4 boards running Qwen Next Flash IQ2_XS at 100k context with around

arXiv:2610.00972v1 Announce Type: new Abstract: As LLM agents undertake increasingly complex, long-horizon tasks, verifying their outputs becomes increasingly challenging. We study how verification ca

arXiv:2610.00833v1 Announce Type: cross Abstract: Fluent LLM explanations may not follow the evidence from a structured system. We present VERITYGATE, a four-gate checker for declared evidence IDs, en

arXiv:2610.00083v1 Announce Type: new Abstract: Humans express uncertainty verbally via markers (e.g., 'possible,' 'likely'), yet most LLM uncertainty quantification (UQ) relies on costing likelihood-

arXiv:2610.00960v1 Announce Type: new Abstract: A video benchmark should reward the capability it claims to measure, yet models can exploit answer options, question text, or partial visual evidence. W

arXiv:2610.00994v1 Announce Type: new Abstract: Existing synthetic image evaluators typically provide only a scalar quality score and do not identify the image regions that support it. We introduce VI

arXiv:2610.00666v1 Announce Type: cross Abstract: Qualitative comparison figures are central evidence in computer vision papers, and vision-language models (VLMs) are increasingly used to judge them.

arXiv:2610.02200v1 Announce Type: new Abstract: We show that multimodal models possess strong reasoning abilities and that an appropriate harness can unlock their potential to solve tasks across diver

arXiv:2610.00350v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) offer an energy-efficient approach to processing event-camera data, yet out-of-distribution (OOD) detection remains chall

arXiv:2610.01512v1 Announce Type: new Abstract: Metal artifacts in postoperative musculoskeletal CT obscure bone-implant and adjacent soft-tissue interfaces. Many metal artifact reduction (MAR) method

arXiv:2610.01499v1 Announce Type: new Abstract: Recent video generation models can produce highly realistic videos from natural language instructions, with visual quality approaching cinematic standar

arXiv:2610.02170v1 Announce Type: cross Abstract: Robots operating in the physical world will increasingly need to coordinate with other robots, particularly in manipulation tasks where an object may

arXiv:2610.01083v1 Announce Type: new Abstract: Vision-language-action (VLA) policies have demonstrated impressive capabilities in generalizable robotic manipulation, but their deployment in the real

arXiv:2610.02000v1 Announce Type: new Abstract: Adverse conditions such as rain, snow, fog, and dust remain challenging for camera-based perception in autonomous driving. We study multi-class weather

arXiv:2610.00749v1 Announce Type: new Abstract: Standard 3D Gaussian Splatting (3DGS) learns geometry and appearance jointly from RGB supervision, making it difficult to isolate how luminance and chro

arXiv:2610.00018v1 Announce Type: new Abstract: Role-specialized QA pipelines increasingly pass rationales from a reasoner to a verifier, but it is unclear what this message actually buys: better answ

arXiv:2610.00366v1 Announce Type: new Abstract: A persistent agent must decide both what to retain as information arrives and what to surface once a query appears, yet memory evaluations can confound

arXiv:2610.00898v1 Announce Type: new Abstract: Biological reasoning models use post-training to connect LLMs to biological foundation model representations and biological text. Their benchmark accura

arXiv:2610.01471v1 Announce Type: cross Abstract: Large language models now generate code, documentation, and analyses, and are increasingly used to review such output. We ask when a second review by

arXiv:2610.01243v1 Announce Type: cross Abstract: Vision-language models (VLMs) increasingly act as judges that pick the best of several generated images, so their choices decide what users see. Such

arXiv:2610.00606v1 Announce Type: cross Abstract: Large Language Models increasingly serve as interfaces for knowledge-intensive information seeking tasks across languages by synthesizing multilingual

arXiv:2610.01425v1 Announce Type: new Abstract: Train-validation separation is the evolving difference between performance on observed training examples and a finite held-out validation set. We propos

arXiv:2610.00713v1 Announce Type: new Abstract: When a graph neural network (GNN) explainer produces an unexpected attribution on a molecule, the attribution alone cannot reveal whether the explainer

arXiv:2610.02162v1 Announce Type: new Abstract: How can a world model continuously observe regions beyond the actor's current view? Video world models simulate how an environment evolves from an agent

Yes! I think there is too much 'we're so early' self-congratulation here. Many senior leaders in companies are smart, motivated, and understand a lot about their business. Many are also technically ad

arXiv:2609.39238v1 Announce Type: new Abstract: An agent that moves must recognise a place from a viewpoint it has never seen. We introduce 4MT-VLM, a dataset of procedurally generated landscapes, eac

arXiv:2609.39058v1 Announce Type: cross Abstract: Reconfigurable Intelligent Surfaces (RIS) are emerging as a key technology for programmable wireless environments in the beyond the fifth generation (

arXiv:2609.39810v1 Announce Type: new Abstract: Source-Free Universal Domain Adaptation (SF-UniDA) extends Universal Domain Adaptation by removing access to source data at adaptation time while still

arXiv:2609.39367v1 Announce Type: cross Abstract: Despite the widespread use of Low-Rank Adaptation (LoRA), little is known about its dynamics in continual learning and the mechanisms by which low-ran

arXiv:2609.39702v1 Announce Type: new Abstract: Adapting a language model to a specialized corpus means choosing which instruction-tuning tasks to train on under a fixed budget, and testing one choice

arXiv:2609.39027v1 Announce Type: new Abstract: AI reviewers can assign different judgments to manuscripts that report the same science in different wording, potentially rewarding rhetorical optimizat

a mod I've been using a lot is 'next-steps' it gives you suggestions on what to do next, including selecting skills and other commands install it with: claude plugin marketplace add anthropics/claude-

arXiv:2609.38561v1 Announce Type: cross Abstract: Zeroth-order optimization methods are essential for solving black-box problems where gradient information is unavailable or expensive to compute. This