model releases

Bagpiper: Solving Open-Ended Audio Tasks via Rich Captions

arXiv:2602.05220v4 Announce Type: replace Abstract: Current audio foundation models typically rely on rigid, task-specific supervision (e.g., speech recognition), addressing isolated factors of audio

Band-Count Dense Modal Estimation with Fixed-Frequency Differentiable Resonator Refinement

DGX agent

arXiv:2608.00667v1 Announce Type: cross Abstract: Task B of the 1st DAFx Parameter Estimation Challenge requires estimating the frequencies, decay rates, gains, and number of modes in a dense plate-re

model-releasesarxiv-cs-lg

4 Aug 2026

Belief-Space Perception Routing under Coupled Sensor Faults and Compute Contention

arXiv:2608.00322v1 Announce Type: cross Abstract: A robot that has to see and react on a fixed clock runs into two problems at once. Its cameras degrade in rain, mud, fog, and darkness. And the single

Benchmarking Sheaf Neural Networks for Inductive Tasks

arXiv:2608.02558v1 Announce Type: new Abstract: Sheaf Neural Networks (SNNs) generalize message passing by replacing scalar edge weights of standard Graph Neural Networks (GNNs) with learnable, edge-d

Beyond Accuracy: Auditing Spatial Provenance in Visual Token Pruning for OCR-Critical MLLM Inference

arXiv:2608.00077v1 Announce Type: new Abstract: Visual-token pruning is usually judged by answer quality at a fixed retention budget. For text-rich multimodal large language models (MLLMs), this proto

Beyond Edge Maps: Wavelet-Domain Conditioning for Multi-Adapter Map-to-Satellite Diffusion

arXiv:2608.00083v1 Announce Type: new Abstract: Commercial mapping partnerships are often unavailable in low-resource regions, leaving satellite basemaps stale and motivating synthesis of satellite im

Beyond Modern Asymptotics for Log-Likelihood Ratios in Logistic Regression

arXiv:2608.02507v1 Announce Type: cross Abstract: We characterize the finite sample behavior of the log-likelihood ratio statistic in binary logistic regression, uniformly over both the design and the

BiKAN: Restoring Collapsed Basis of Binary Kolmogorov--Arnold Networks

arXiv:2608.01490v1 Announce Type: new Abstract: Binarizing a polynomial Kolmogorov--Arnold Network (KAN) not only changes parameter precision, but also alters the function space available to each laye

Boosting Generalizable Depth Estimation in Endoscopy by Mixture of Lightweight Experts and Intrinsic Image Alignment

arXiv:2608.00415v1 Announce Type: new Abstract: Depth estimation is a significant task for 3D perception in endoscopic surgeries. However, illumination interference and feature diversity in various en

Breaking the Horizontal Prior: From Long-Tailed Orientation Bias to Roll-Robust Monocular Depth Estimation

arXiv:2608.00678v1 Announce Type: new Abstract: Despite recent advances in Monocular Depth Estimation, state-of-the-art depth foundation models remain vulnerable to robustness issues. Particularly, ev

Bridging the English-Arabic Medical Knowledge Gap: Targeted Low-Rank Adaptation via Causal Layer Selection

arXiv:2608.00207v1 Announce Type: new Abstract: Large Language Models (LLMs) perform strongly in English medical tasks but degrade substantially in Arabic, a gap widely attributed to limited training

BRiG-AFA: Bellman Risk-to-Go Learning for Non-Myopic Active Feature Acquisition

arXiv:2608.02305v1 Announce Type: new Abstract: Active feature acquisition (AFA) asks which unobserved feature to measure next for each test instance under a budget. Greedy rules are easy to train but

CADENA: Stepwise CAD Reverse Engineering

arXiv:2608.00799v1 Announce Type: new Abstract: Computer-Aided Design (CAD) underpins modern engineering, yet converting existing shapes into editable models still demands substantial expert effort. M

Can You Trust the Confidence? ConfBench for Vision-Language Models on Document Extraction

arXiv:2608.01792v1 Announce Type: cross Abstract: Intelligent document processing (IDP) with vision-language models (VLMs) hinges on confidence scores trustworthy enough to route extractions between a

Capability Provenance in Language Models: A Case Study in Social Reasoning

arXiv:2606.19625v2 Announce Type: replace Abstract: We use training-data attribution as an interpretable tool for capability discovery, mapping which regions of the pretraining corpus support social-r

CAPEval: A Decoupled Caption Evaluation across Understanding and Generation

arXiv:2608.02589v1 Announce Type: new Abstract: Captions serve as a primary supervision signal for both multimodal understanding and text-to-image generation. However, previous evaluations treat the c

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments

arXiv:2509.06419v2 Announce Type: replace Abstract: Time-series anomaly detection is crucial in AIOps for maintaining large-scale service reliability. In production, streams of Key Performance Indicat

Certifying Plans under Model Mismatch: A Trilemma for Reachability from Scarce Data

model-releasesarxiv-cs-ro

arXiv:2608.02453v1 Announce Type: new Abstract: Sim-to-real policies are designed under nominal dynamics, but target-system trials may yield only a few isolated one-step transitions. We study pre-exec

ChainVLA: Chaining Vision-Language-Action Queries through a Unified Execution State for Long-Horizon Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.02326v1 Announce Type: new Abstract: Humans perform long-horizon manipulation by retaining knowledge of what earlier actions have established while continuously adapting the motion underway

ChaosProbe: A Neurochaotic Lens on Frozen Transformer Input-Embedding Spaces

arXiv:2608.01968v1 Announce Type: new Abstract: Transformer models are most often understood through what they do: their benchmark performance, generation quality, or behavior on downstream tasks. Yet

CHOW-SLAM: Compact Hybrid Representation with Complementary Overlap Window Optimization for RGB-D SLAM

arXiv:2608.01914v1 Announce Type: new Abstract: Simultaneous localization and mapping (SLAM) based on Neural Radiance Fields (NeRF) enables dense, continuous scene reconstruction. However, existing sy

Cluster-Aware Over-the-Air Federated Learning with Energy-Harvesting Devices: From Global Training to Model Personalization

arXiv:2608.01426v1 Announce Type: new Abstract: Federated learning (FL) enables distributed optimization and learning across decentralized edge devices while preserving data privacy, but its performan

CompanionBench: A Theory-Anchored, Real-World-Grounded Benchmark for AI Emotional Companionship

arXiv:2608.02046v1 Announce Type: new Abstract: LLM companions are deployed at scale in personally consequential settings, yet poorly evaluated. Existing benchmarks use hand-authored scenarios and pro

Company approved 128GB Mac for research proposal, best model?

model-releasesr-localllama

I‘m doing a research proposal at my company about running local LLMs to replace daily coding models. Qwen 3.6 27B (or 3.8 potentially) is widely seen as the best model in that 20-60GB space, is that s

CoNav-UAV: Cooperative Dual-Altitude Aerial Navigation via Stackelberg Learning

model-releasesarxiv-cs-ro

arXiv:2608.01802v1 Announce Type: cross Abstract: Target-oriented vision-and-language navigation (VLN) on aerial platforms is attracting growing attention for missions such as disaster rescue, infrast

Conditional Deep Levy Models for Exotic Derivatives: History-Aware Path Generation and P-Q Payoff Diagnostics

arXiv:2509.13374v2 Announce Type: replace-cross Abstract: We develop and audit a history-aware financial path generator based on Denoising Levy Probabilistic Models (DLPMs) for conditional equity-inde

Conservation laws determine what physical learning remembers

arXiv:2608.00097v1 Announce Type: cross Abstract: Physical learning rules such as equilibrium propagation (EP), coupled learning (CL), and adjoint coupled learning (AL) train resistive networks throug

Control Under Compression: Reliability Frontiers for Tool-Using Agents

arXiv:2608.01056v1 Announce Type: cross Abstract: Tool-using language-model agents are governed not only by task prompts but also by persistent system-side instructions that specify tools, arguments,

Cooperative Coevolution for Resource-Constrained Agentic LLM Post-Training

arXiv:2608.02391v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents produce long, multi-turn trajectories, making gradient-based post-training memory-intensive. Evolution st

CORTIVA: Candidate-Score Fusion of Complementary Visual Teachers for EEG- and MEG-to-Image Retrieval

arXiv:2608.01355v1 Announce Type: new Abstract: Decoding visual experience from non-invasive brain activity is central to neuroscience and brain-computer interfaces. Functional magnetic resonance imag

Cost-Effective Automated Judging of Natural-Language Mathematical Proofs

arXiv:2608.00004v1 Announce Type: new Abstract: Grading natural-language mathematical proofs is a recurring cost in evaluating math-reasoning systems, and frontier LLM judges are expensive. We ask whe

CoSynFlow: Conformal Symplectic Neural Flows for Cross-System Prediction of Dissipative Hamiltonian Dynamics

arXiv:2608.00571v1 Announce Type: new Abstract: Learning solution operators for differential equations is a central problem in scientific machine learning. However, many neural operator methods optimi

CRAFT: Compression via Recursive Adaptive Fusion of Video Tokens for Vision-Language Models

arXiv:2608.01644v1 Announce Type: new Abstract: In video understanding, vision-language models (VLMs) must ingest massive numbers of visual tokens, causing the computational and memory cost of the pre

CRIP: Channel Level Representation Injection for Personalized One-Shot Federated Learning

arXiv:2608.02222v1 Announce Type: new Abstract: One-shot federated learning (OSFL) has emerged as a promising collaborative model learning framework with only a single round of communication, offering

CrossLex: A Source-Grounded Benchmark for Cross-Jurisdictional Legal Reasoning in Large Language Models

arXiv:2608.01292v1 Announce Type: new Abstract: Legal reasoning is inherently jurisdiction-dependent: the same facts can call for different legal rules and yield different conclusions across legal sys

CrossProjection: Geometric Grounding Beyond Viewpoint Change in Architectural Drawings

arXiv:2608.00473v1 Announce Type: cross Abstract: Architectural drawings violate the usual assumption behind multi-view reasoning: plans and sections are cuts, while elevations are facade projections,

Crushing the Evidence: A Dual-Penalty Evasion Framework for Fooling White-Box Explainable AI Auditors

arXiv:2608.00566v1 Announce Type: new Abstract: Post-hoc model explainers such as LIME, SHAP, and Integrated Gradients are widely deployed to audit models in high-stakes sensitive domains, including f

CultureVidBench: Benchmarking Cultural Understanding in Text-to-Video Generation

arXiv:2608.01942v1 Announce Type: cross Abstract: Text-to-video (T2V) generation models have advanced rapidly, yet their ability to represent diverse cultural contexts remains underexplored. Existing

CurveShift: Is Agent Progress Scalar? Separating Level from Shape

arXiv:2608.00355v1 Announce Type: new Abstract: Progress in large language models is often summarized using a single scalar measure, such as a time horizon, a latent ability estimate, or an aggregate

Data-Driven Pinball-Loss Selection for Vertically Distributed Elastic-Net SVMs

arXiv:2608.00949v1 Announce Type: new Abstract: The pinball-loss support vector machine is robust, but its asymmetry parameter is usually fixed in advance. We propose a data-driven elastic-net support

DE-NER : Zero-shot Named Entity Recognition via Dialogue Elicitation of Large Language Models

arXiv:2608.00538v1 Announce Type: new Abstract: Recent advancements of zero-shot Named Entity Recognition (NER) establish strong baselines by formulating sequence labeling into question answering wher

DeBERTa-Sentinel: Toward Transparent and Trustworthy Detection of AI-Generated Text

arXiv:2608.01046v1 Announce Type: new Abstract: The rapid spread of large language models (LLMs) across the web raises concerns about misinformation, academic integrity, automated content manipulation

DeCLIP: Decoupled Prompting for Multi-Label Class-Incremental Learning with CLIP

arXiv:2509.23335v3 Announce Type: replace Abstract: Multi-label class-incremental learning (MLCIL) continuously expands the label space while recognizing multiple co-occurring categories, making catas

Decoupling semantics from vision: A framework for faithful visual-text compression evaluation

arXiv:2608.01848v1 Announce Type: new Abstract: Recent visual-text compression (VTC) methods, typified by DeepSeek-OCR, report impressive high token compression ratios for long-context modeling tasks

Decrease the power limit of your 5090 to at least 480W - the performance penalty for inference is negligible.

model-releasesr-localllama

I run my inference machine in the living room, so noise and heat output are a significant concern. Ran a quick test using my daily driver model (Qwen 3.6-27b) and at 480W, the card outputs only 2.1% l

Deep Learning for Cyber Threat Detection and Mitigation in Healthcare-IoT

arXiv:2608.00118v1 Announce Type: cross Abstract: Cybersecurity is a fundamental requirement for protecting wearable devices used in healthcare Internet of Things (H-IoT) systems. Security failures in

Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challenge

arXiv:2506.02976v4 Announce Type: replace Abstract: The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) thro

[Deepseek-V4-Flash-0731] Full 1M context on a single RTX5090 + DDR5 Desktop Setup with VLLM CPU/Ram Offloading, ~800 tps pp & 15+ tps decode [Agentic Coding]

model-releasesr-localllama

First of all, obviously I took some help from AI to type this post and this is the topic that enabled me to accomplish all that: https://old.reddit.com/r/LocalLLaMA/comments/1veow4b/deepseek_v4flash_2