model releases

PACEShop: Evaluating Personalized, Actionable, Compositional, and Evidence-grounded Shopping Assistants

arXiv:2608.26180v1 Announce Type: cross Abstract: Shopping assistants are shifting from ranked product lists toward structured decision support, where systems must synthesize shopper context, product

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Parameter Efficient Continual Learning for Sparse Event-Based Transformers

DGX agent

arXiv:2608.26720v1 Announce Type: new Abstract: Robotic and edge intelligence systems operate in dynamic environments where data arrives continuously, requiring models to adapt while preserving previo

model-releasesarxiv-cs-cv

28 Aug 2026

Parameter-Efficient pretrained-CT-to-MRI Transfer for Rectal Cancer Segmentation: Performance-Calibration Trade-offs

arXiv:2608.27178v1 Announce Type: new Abstract: Accurate rectal cancer segmentation from magnetic resonance imaging (MRI) is essential for adaptive radiotherapy and tumor response assessment, but depl

PAWBench: How Far Are We from Probabilistically Aligned World Modeling?

arXiv:2608.27345v1 Announce Type: cross Abstract: Recent video generation models are increasingly framed as world models. Many physical processes can unfold in more than one valid way. Therefore, a wo

Performance Foundations of Parallel & Distributed Reasoning Language Models

arXiv:2608.27046v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) and other RL-style post-training paradigms have been used for aligning large language models (LL

Physics-Informed Stochastic Configuration Machine: A Backpropagation-Free Neural Network with Fast Training for Nonlinear Differential Equations

arXiv:2608.26549v1 Announce Type: cross Abstract: While Physics-Informed Neural Networks (PINNs) have emerged as a transformative paradigm for solving complex differential equations, their reliance on

PICasso: An AI-Enabled Design Framework for Autonomous Optimization of Silicon Photonic Devices

arXiv:2608.26113v1 Announce Type: new Abstract: We present PICasso, an AI-assisted framework for automated synthesis, verification, and optimization of photonic integrated circuits (PICs) from natural

Plain Transformers Can be Powerful Graph Learners

arXiv:2504.12588v4 Announce Type: replace-cross Abstract: Transformers have attained outstanding performance across various modalities, owing to their simple but powerful scaled-dot-product (SDP) atte

Prediction of Prediction (PoP): Inter-Layer Activation Fusion for Single-Pass Hallucination Detection in Large Language Models

arXiv:2608.27165v1 Announce Type: new Abstract: Autoregressive large language models (LLMs) routinely generate factually incorrect outputs with high decoding confidence, limiting their deployment in h

PredVLA: A Sub-Million-Parameter Predictive-Coding Policy for Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.26673v1 Announce Type: new Abstract: Large pretrained vision-language-action models dominate modern robot-manipulation benchmarks, but it remains unclear how much model scale is necessary f

Privacy Without Regret: Differentially Private Inference-Time Alignment

arXiv:2608.26324v1 Announce Type: new Abstract: Best-of-N (BoN) sampling is the simplest and most widely deployed inference-time alignment strategy, but it suffers from two distinct problems: reward h

Procedura: Agentic 3D Modeling with Procedural Control

arXiv:2608.26238v1 Announce Type: new Abstract: Native 3D generators now recover impressive mesh geometry from a single image. However, a dense mesh stays soft where a machined object should be sharp,

Profit based evaluation of machine learning for nitrogen recommendations in winter wheat

arXiv:2608.27205v1 Announce Type: new Abstract: Nitrogen rates for winter wheat are set before the season, under unknown prices and weather. The standard UK advice does not respond to prices, yet rece

Puro-2B: Poor Lab's Qwen2-1.5B Trained on RTX 5090 within $5090

arXiv:2608.27370v1 Announce Type: new Abstract: Language model pretraining has become almost synonymous with prohibitive cost, placing it out of reach for much of the academic and open-source communit

QuantumBoostNet: A Hybrid Classical-Quantum Architecture for Enhanced Accuracy in Cardiac Ultrasound View Identification

arXiv:2608.27302v1 Announce Type: new Abstract: Accurate identification of the correct view or angle in cardiac ultrasound (echocardiogram) is a critical component of cardiologic imaging. This step is

Qwen3.8-27B on a 24GB RTX PRO 4000 Blackwell: 128K real context, 785 tok/s prefill, 67 tok/s MTP3 decode

I wanted to see whether NInfer could run Qwen3.8-27B on an RTX PRO 4000 Blackwell 24GB. Hardware/software: NVIDIA RTX PRO 4000 Blackwell, 24GB 145W power limit CUDA 13.3 NVIDIA driver 610.x Ubuntu LXC

Qwen3.8-27b q8 KV cache does seem to actually hurt model performance

EDIT: Though the issue with q8 kv cache seems to arise from when and how often we run the quantize step, not that kv quantizing can't ever work - see comments for various proposed solutions --- One of

Qwen3.8-Flash-Next (UD-IQ4_XS) on 2x RTX 3060 + 7800X3D, from initial 36 tps prefill to 400 tps and other benchmarks (-sm tensor trap) + VRAM/RAM usage

TL;DR: llama.cpp with --load-mode mmap used 21-32 GB of RAM, with ik_llama.cpp using 106-108 GB. -sm tensor killed my prefill, changing to -sm layer went from 36 tps to 135 tps. After that, -ubatch 20

Qwen3.8-Flash on RTX3090 + 64GB RAM (but you only need 12GB VRAM)

I've got Qwen3.8-Flash-next running on RTX 3090, Ryzen 9 3950X, a PCIe 3.0 motherboard, and 64GB DDR RAM from 2020. IQ4_XS weights, full kvarn5 context, vision on GPU, experts in host RAM, n-grams on

R2M-Bench: Evaluating Revisit Memory via Relative Consistency in Interactive Video World Models

arXiv:2608.27328v1 Announce Type: new Abstract: High similarity between first-visit and return frames does not necessarily show that a video world model remembered the scene; the intervening rollout m

RATIO: A Benchmark for Retrieval Across Typed Ideation Operations in Scientific Literature

arXiv:2608.27394v1 Announce Type: new Abstract: Retrieved scientific literature can serve as inspiration for both human and AI scientists. Inspiration can take different forms: prior work may directly

Real-time Unsupervised Object Discovery from Asynchronous Event Streams

arXiv:2608.26644v1 Announce Type: new Abstract: Event cameras capture pixel-level intensity changes with microsecond resolution to produce highly sparse asynchronous data streams. For visual perceptio

Redwood: A Frontier AI Accelerator Designed, Verified, and Deployed from Scratch in 2 Weeks by AI

arXiv:2608.26418v1 Announce Type: cross Abstract: Modern AI workloads and the hardware that runs them evolve on different timescales: architectural definition precedes volume silicon by years, while t

Refusal Is Not Robustness: Auditing Confident Fabrication in Large Language Models on a Provably Uninformative Clinical Pain Speech Transcript

arXiv:2608.26167v1 Announce Type: new Abstract: Hallucination and abstention benchmarks rarely establish that a model could not have known the correct answer, making it difficult to distinguish approp

[Release] SOTA GGUFs for Qwen3.8-27B: GSQ-RCO at 2.5 to 3.0 bpw

We're releasing Qwen3.8-27B quantized with our newest methods, GSQ + RCO. Higher-quality models, same file size, now with the search and the quantizer both learned. What's inside: GSQ (Gumbel-Softmax

Rethinking Image Processing for the Age of AI: A Problem-First Framework for Scientific Progress

arXiv:2608.26833v1 Announce Type: new Abstract: Modern AI has greatly expanded the capabilities of image processing. However, the ready availability of powerful models, public datasets, and benchmark

ReViCo: Unveiling the Limitations of VLMs in Visual Text Understanding via Error Correction

arXiv:2608.27154v1 Announce Type: new Abstract: Vision Language Models (VLMs) have shown great success in general visual tasks, yet they still struggle to deeply understand text within images. In this

Reward-Informed Sparse Autoencoders and the Solution-Completeness Confound

arXiv:2608.26136v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) decompose language-model activations into sparse, interpretable features, and an appealing way to aim them at reasoning is to

Riemann-1.0: An Embodied World Action Model for Physical AI

model-releasesarxiv-cs-ro

arXiv:2608.27033v1 Announce Type: new Abstract: We introduce Riemann-1.0, a fully causal autoregressive World Action Model for embodied intelligence. Riemann-1.0 jointly models multi-view visual obser

ROCm 10.0: A Decade of Open Compute, Built for the Age of Agentic AI

Their last version 7.14 was released just a month ago. llama.cpp PR(waiting for approval) for Version 10.0 https://github.com/ggml-org/llama.cpp/pull/27803 Hope this version comes with more boost & im

RuleWeaver: Benchmarking Rule-Centered Scenario Reasoning for Large Language Models

arXiv:2608.26832v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied to specialized domains, where effective use of domain expertise often requires reasoning over comp

Said Aloud, Read Different: Cross-Modal Instability in Multimodal Models

arXiv:2608.27135v1 Announce Type: new Abstract: Multimodal foundation models are increasingly used in speech-first assistants that must interpret spoken queries and produce visually grounded decisions

SecureDrive-FL: Joint Differential Privacy and Gradient-Aware Selective Homomorphic Encryption for Federated Driver Monitoring

arXiv:2608.27108v1 Announce Type: cross Abstract: Federated Learning (FL) enables privacy-aware distributed training, yet gradient updates remain exploitable: Man-in-the-Middle (MitM) interception exp

Selective State-Space Adaptation and Retrieval for Language Model Reasoning

arXiv:2607.19326v2 Announce Type: replace Abstract: Low-rank adaptation introduces a static learned update applied identically to every input. The update provides task-level adaptation but does not ex

SLM-Conditioned Hierarchical Relation Routing for Labeled Property Graph Learning

arXiv:2608.26132v1 Announce Type: cross Abstract: Labeled property graphs combine relational structure with heterogeneous textual and categorical properties attached to both nodes and relationships. C

SpatialCrafter: Single Image World Modeling with Generative 3D Proxies

arXiv:2608.27073v1 Announce Type: new Abstract: Explorable image-to-scene generation is essential for applications in gaming, robotics, and virtual reality. Existing methods based on video diffusion m

SpeechGym: An Audio-Native Gym for Training Voice Agents via Reinforcement Learning

arXiv:2608.26432v1 Announce Type: cross Abstract: Voice agents must call tools and hold multi-turn dialogue entirely through speech, yet the dominant paradigm trains them in text. Existing frameworks

Spreading the load: How Salesforce met Multi-AZ HA with SageMaker Inference Components

model-releasesaws-ml-blog

Learn how Salesforce used Amazon SageMaker AI Inference Component placement (the SchedulingConfig parameter) to distribute model copies across multiple Availability Zones, meeting their Multi-AZ high

Squeezing More from Limited Data with Recursive Transformers

arXiv:2608.26973v1 Announce Type: new Abstract: Pre-training under limited data requires a different view of scaling than web-scale language modeling. With a fixed data budget but relatively abundant

StreamAV-Bench: A Comprehensive Benchmark for Streaming Audio-Video Generation

arXiv:2608.26336v1 Announce Type: cross Abstract: Recent advancements in generative models are pushing video generation toward unbounded streaming audio-video generation for real-time interactive worl

Subgraph Filtering for Fair Graph Neural Networks

arXiv:2608.26437v1 Announce Type: new Abstract: Graph neural networks (GNNs) can exhibit unfair behavior even when sensitive attributes are excluded from node features, because graph topology and mess

Successive Capacity Growth: Task-Complexity-Driven Width and Depth Expansion for Vision Transformer Encoders in JEPA World Models

arXiv:2608.27367v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) for world modeling typically employ fixed-size Vision Transformer encoders that are over-provisioned

Syntax vs. Semantics: How Transformers Learn Deep Dependencies

arXiv:2608.26139v1 Announce Type: cross Abstract: Large Language Models demonstrate remarkable syntactic fluency, yet the optimization dynamics governing their acquisition of deep semantic dependencie

SynthCharge: An Electric Vehicle Routing Instance Generator with Feasibility Screening to Enable Learning-Based Optimization and Benchmarking

arXiv:2603.03230v2 Announce Type: replace-cross Abstract: The electric vehicle routing problem with time windows (EVRPTW) extends the classical VRPTW by introducing battery capacity constraints and ch

TabuLM: Morphology-Aware Tabular Pre-training for Low-Resource Languages

arXiv:2608.26923v1 Announce Type: new Abstract: We present TabuLM, the first language model pre-trained on Kinyarwanda tabular data. Kinyarwanda is a morphologically rich Bantu language spoken by over

TADP: Task-Aware Deformable Prediction for Single-Stage 3D Object Detection

arXiv:2608.27282v1 Announce Type: cross Abstract: Most single-stage 3D object detectors complete different tasks with the same extracted features. Nevertheless, it is impossible to project features in

TempJail: Temporal Jailbreak Attacks against Image-to-Video Generation Models

arXiv:2608.26971v1 Announce Type: new Abstract: In recent years, image-to-video (I2V) generation models have made remarkable progress in subject consistency and temporal coherence, enabling high quali

Temporally-Grounded Language Generation: Towards Real-Time Vision-Language Models

arXiv:2505.11326v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have shown remarkable progress in offline tasks such as image captioning and video question answering. However,