Search: “models”

LogicIF: Towards Complex Logic Instruction Following

arXiv:2508.09125v4 Announce Type: replace Abstract: Instruction following has catalyzed the recent era of Large Language Models (LLMs) and is the foundational skill underpinning more advanced capabili

Applications

Mask-aware inference with State-Space Models

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DGX agent

arXiv:2603.04568v2 Announce Type: replace Abstract: Many real-world computer vision tasks, such as depth completion, must handle inputs with arbitrarily shaped regions of missing or invalid data. For

applicationsarxiv-cs-cv

11 Aug 2026

MultiShadow: Multi-Object Shadow Generation for Image Compositing via Diffusion Model

arXiv:2603.02743v4 Announce Type: replace Abstract: Realistic shadow generation is crucial for achieving seamless image compositing, yet existing methods primarily focus on single-object insertion and

safetyarxiv-cs-cv

NVIDIA Nemotron 3.5 Lightning and NeMo Switchyard Deliver Faster, Smarter, More Efficient Agentic AI

model-releasesnvidia-blog

As AI shifts from chatbots to autonomous agents, open models are serving market demands for full control over where AI runs and how it’s deployed and evolves. Today, NVIDIA is expanding its Nemotron 3

Nvidia releases Nemotron 3.5 Lightning and NeMo Switchyard to give enterprise AI capability options

model-releasessiliconangle

Artificial intelligence silicon and software giant Nvidia Corp. today announced two new services: a highly customizable Nemotron model and an agentic AI model router named NeMo Switchyard. As enterpri

Out-of-Distribution Federated Distillation with Domain-Aware Proxy

arXiv:2608.08525v1 Announce Type: new Abstract: Federated Learning is a distributed machine learning paradigm that trains a global model by aggregating local clients without sharing private data of ea

Proxy OPD: On-Policy Distillation with Transferable Relative Proxy Update

arXiv:2607.11505v2 Announce Type: replace-cross Abstract: Post-training for large language models typically couples policy exploration with model optimization, hindering the reuse of high-reward behav

safetyarxiv-cs-ai

Real Data Closes Synthetic-to-Real Gap in Optical Chemical Structure Recognition

arXiv:2608.09100v1 Announce Type: cross Abstract: Millions of chemical structures appear in patents and papers only as drawings, and using that information at scale requires reading the drawings. OCSR

Reproducing and Stress-Testing Two Approaches to LLM Reasoning Reliability: Test-Time Probability Aggregation and Logic-Representation Editing

arXiv:2608.08514v1 Announce Type: new Abstract: We independently reproduce two recent methods for making large language model (LLM) reasoning more reliable, and stress-test them across domains and mod

Local Ai

Scale-to-Dialogue: Low-Burden Elicitation of Daily Premenstrual Symptom Ratings with Small Language Models

arXiv:2608.08746v1 Announce Type: new Abstract: Prospective daily symptom tracking is central to premenstrual health assessment, but repeated ordinal forms impose substantial response burden. We formu

local-aiarxiv-cs-ai

SHE: Trajectory-driven Safety Harness Evolution for LLM Agents

arXiv:2608.09885v1 Announce Type: new Abstract: The safety of large language model (LLM) agents depends not only on model weights but also on the agent harness that manages context, memory, tools, per

Sparks of Cooperative Reasoning: LLMs as Strategic Hanabi Agents

arXiv:2601.18077v3 Announce Type: replace Abstract: Cooperative reasoning under incomplete information remains challenging for both humans and multi-agent systems. The card game Hanabi embodies this c

Stateful CARS: Exact Cross-History Reuse for Policy-Constrained LLM Agents

arXiv:2608.08282v1 Announce Type: new Abstract: Tool-using language-model agents face constraints whose meaning changes with observations and prior actions. We study exact sampling from the model dist

Agents

STEMMA: An Adversarial Multi-Agent Framework for Evaluating Self-Identity Consistency in LLMs

arXiv:2608.08164v1 Announce Type: cross Abstract: Knowledge Distillation is a widely adopted technique in the training and fine-tuning of large language models (LLMs) enabling transfer of structured i

agentsarxiv-cs-ai

SUMI: Scalable Unified Model for 3D Point Cloud Inference

arXiv:2608.08115v1 Announce Type: new Abstract: Point cloud completion commonly follows a coarse-to-fine paradigm, where a low-density coarse shape is first predicted and then upsampled to the target

researcharxiv-cs-cv

SynVAR: Synergizing Spatial and Semantic Alignment in Visual Autoregressive Model

arXiv:2608.07948v1 Announce Type: new Abstract: VAR has gained widespread popularity due to its next-scale prediction paradigm. However, it faces substantial performance bottlenecks when handling comp

safetyarxiv-cs-cv

Tested in Coding: BF16 Muse Glimmer vs BF16 Qwen3.6 27B

model-releasesr-localllama

I'm guessing that many people have been waiting for this comparison. For clarity, both models are running at full FP16 KV-cache. Due to VRAM limitations, Muse Glimmer is running full 262,144 context,

Think Deep, Speak Once: Relit, A Recursive Latent Implicit Transformer Framework

arXiv:2608.08113v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting has become the dominant paradigm for eliciting reasoning in Large Language Models (LLMs), yet it creates substantial co

To Memorize or to Retrieve: Scaling the Interaction Between Pretraining and Retrieval

arXiv:2604.00715v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) improves language model (LM) performance by providing relevant context at test time for knowledge-intensi

Wiener Representation Filtering for VLM Hallucination Suppression

arXiv:2608.08167v1 Announce Type: new Abstract: Vision-language models (VLMs) excel at open-ended captioning and visual QA but often describe objects, attributes, or relations absent from the image, a

A Multi-Agent Framework for Automated Coarse-Grained Molecular Dynamics of Polymers

arXiv:2608.06694v1 Announce Type: new Abstract: Coarse-grained (CG) molecular dynamics extends polymer simulation beyond the scales accessible to all-atom (AA) methods, but bottom-up CG modeling is la

Does More Retrieved Evidence Help Visual Retrieval-Augmented Generation with Diffusion Language Models?

arXiv:2608.07006v1 Announce Type: new Abstract: Visual retrieval-augmented generation (RAG) commonly expands the retrieved evidence set to improve answer-page coverage, implicitly assuming that all av

researcharxiv-cs-cl

Free Denoising Diffusion Models

arXiv:2510.22778v3 Announce Type: replace-cross Abstract: We develop a free-probabilistic framework for denoising diffusion, in which the data is a self-adjoint operator and its law a spectral distrib

researcharxiv-cs-lg

HLSmith: An Expert-Guided Agentic Framework for C/C++-to-HLS Translation

arXiv:2608.06791v1 Announce Type: cross Abstract: Application-specific FPGA accelerators offer substantial performance and energy-efficiency gains across many application domains, but developing them

Latent Fact-Checking: Detecting Misinformation through Activation Engineering

arXiv:2608.06417v1 Announce Type: cross Abstract: The proliferation of misinformation online has driven demand for scalable detection systems. While most existing approaches rely on surface-level ling

Need real world ML problems to evaluate my educational ML tools

model-releasesr-localllama

I'm a retired platform engineer, coding mainly in Rust, and involved with a ML study group. I developed a ML programming language (alternative to Python, Colab) to help me learn (and teach) ML concept

Local Ai

omlab/VLX-Seek-1.5-10B · Hugging Face

VLX-Seek-1.5-10B VLX-Seek-1.5-10B is the open-source 10B model in the VLX-Seek 1.5 family, designed for fine-grained perception and visual grounding in embodied scenarios. It targets practical setting

local-air-localllama

Test-Time Adaptation with Online Personalized Energy-Based Cache for Fine-Grained Video Expression Recognition

arXiv:2608.06467v1 Announce Type: new Abstract: Facial expression recognition (FER) in videos is challenging because models must identify subtle, temporally evolving affective states that vary across

UniREditBench: A Unified Reasoning-based Image Editing Benchmark

arXiv:2511.01295v3 Announce Type: replace Abstract: Recent advances in multi-modal generative models have driven substantial improvements in image editing. However, current generative models still str

v0.32.7

model-releasesollama-releases

Muse Glimmer Note: Muse Glimmer is currently available via initial support via Ollama's MLX engine on Apple Silicon. Additional support and optimizations for Apple Silicon, NVIDIA, AMD, and other plat

A Foundational EDM2-Based Generative Model for High-Resolution Synthetic Fetal Ultrasound Imaging from Open Datasets

arXiv:2608.05471v1 Announce Type: cross Abstract: Prenatal ultrasound imaging is key for assessing fetal health, but AI progress is limited by scarce, privacy-restricted, and hard-to-annotate datasets

researcharxiv-cs-cv

A Two-Tier Perspective on Inference-Time Parallelism in Multi-Agent LLM Systems

arXiv:2608.05791v1 Announce Type: cross Abstract: Large language model (LLM)-driven multi-agent systems typically require multiple model invocations and complex coordination during inference, and thei

Agents

Agentic Software Issue Resolution with Large Language Models: A Survey

arXiv:2512.22256v2 Announce Type: replace-cross Abstract: Software issue resolution aims to address real-world issues in software repositories based on natural language descriptions provided by users,

agentsarxiv-cs-ai

Deterministic World Models for Closed-loop Reachability Analysis of End-to-End Vision-based Control

arXiv:2512.08991v3 Announce Type: replace Abstract: End-to-end image controllers that map raw camera frames directly to control actions are increasingly deployed in safety-critical systems. However, f

safetyarxiv-cs-cv

Learning When to Trust via Selective Context Preference Optimization

arXiv:2608.06377v1 Announce Type: cross Abstract: Language models increasingly condition their answers on external signals, and a single misleading one can turn a correct answer wrong. The obvious rem

Otter: A Time-Aware, History-Conditioned Human Chess AI

arXiv:2608.05206v1 Announce Type: new Abstract: Otter is a 15.3M-parameter human chess AI that predicts human move selection by modeling play as a time-aware, sequential process rather than treating e

Reducing belief in conspiracy theories as they unfold using large language models

arXiv:2608.06151v1 Announce Type: cross Abstract: The emergence of conspiracy theories in the wake of major events is a significant societal challenge. Here we test whether conversational dialogues wi

researcharxiv-cs-ai

Runtime Observability for Heterogeneous Attention Memory

arXiv:2608.05863v1 Announce Type: new Abstract: Modern models no longer keep a plain KV cache: latent caches, learned sparse selectors and recurrent states each carry the model's memory in a different

Scientific Machine Learning of Chaotic Systems Learns Reduced-Order Equations for Neural Populations

arXiv:2507.03631v4 Announce Type: replace Abstract: Extracting interpretable mathematical models from complex dynamical systems is difficult, especially for chaotic dynamics observed with noisy experi

SkillMemo: Expert-guided Skill Memory Framework for Compositional Embodied Manipulation

arXiv:2608.05970v1 Announce Type: cross Abstract: Embodied visuomotor models, including Diffusion Policy (DP) and Vision-Language-Action (VLA) models, have demonstrated promising performance on roboti

TS-RAG: Retrieval Augmented Generation for Time Series Forecasting

arXiv:2608.06223v1 Announce Type: new Abstract: While deep learning models, particularly transformer-based architectures, have shown impressive performance in time series forecasting, the application

Beyond Boundary Frames: Talking-Head Inbetweening via Context-Aware Motion Modeling

arXiv:2512.03590v3 Announce Type: replace Abstract: Existing talking-head generation methods primarily target open-ended generation rather than bridging two existing video segments. In this paper, we

researcharxiv-cs-cv

Eliciting Intrinsic Hallucinations in LLMs via Semantically Equivalent Adversarial Attacks

arXiv:2608.04286v1 Announce Type: new Abstract: Large language models (LLMs) are often used in conjunction with external knowledge sources to improve their factual accuracy and decrease hallucinations

Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features

arXiv:2608.04379v1 Announce Type: cross Abstract: We propose a method to optimize the correlation among convolutional neural network (CNN) features that are used as inputs to quantum neural network (Q

researcharxiv-cs-ai

Meta’s Muse Spark 1.1 hacked an external organization during cybersecurity test

model-releasessiliconangle

A large language model developed by Meta Platforms Inc. hacked a third party organization during a cybersecurity evaluation. The Facebook parent disclosed the incident on Wednesday without specifying

Mirendil taps AI Hypercomputer TPUs and GPUs for pre- and post-training applications

model-releasesgoogle-cloud-ai

Nearly every major AI lab uses Google Cloud infrastructure, including for training of models, inference for agents, and new frontier research. Google Cloud also continues to be the platform of choice

nvidias nemotron omni only loads its text half on a mac, so i wrote the vision and audio towers in mlx

model-releasesr-localllama

nvidias nemotron omni is open weights and it sees, hears and reasons. theres already a 4bit mlx quant on hugging face but only the text backbone loads with standard mlx tooling. the model card says it

One Surrogate to Fool Them All: Universal, Transferable, and Targeted Adversarial Attacks with CLIP

arXiv:2505.19840v3 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) have achieved widespread success yet remain prone to adversarial attacks. Typically, such attacks either involve f