Search: “models”

Modular TTT: Rethinking Test-Time Training as Composable Modules

arXiv:2608.07110v1 Announce Type: cross Abstract: Test-time training (TTT) views sequence modeling as an online learning problem in which fast weights are updated by an internal learning rule. Despite

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MultiView-Bench: A Diagnostic Benchmark for World-Centric Multi-View Integration in VLMs

DGX agent

arXiv:2607.08970v2 Announce Type: replace-cross Abstract: Recent benchmarks for VLMs largely assess single- or limited-view perception, leaving untested the core cognitive ability to integrate observa

model-releasesarxiv-cs-ai

10 Aug 2026

metaopen-weightslocal-models

Muse Glimmer

Human

Meta's Apache-2.0 30B Muse Glimmer targets local agentic tool use, multi-step coding, and vision, sized to leave headroom on 32GB machines.

PURe: A Plug-and-Play Product-Unit Residual Module for Vision Networks

arXiv:2505.04397v3 Announce Type: replace-cross Abstract: Modern vision networks are dominated by additive local transformations, whereas explicit multiplicative local interactions remain underexplore

Safety

Representation-driven Endoscopic Visual Embedding Alignment for Latent Generation

arXiv:2608.07176v1 Announce Type: cross Abstract: Developing foundation generative models for endoscopy is limited by the gap between natural and clinical images and the computational cost of training

safetyarxiv-cs-ai

Safety

Representation Handoffs for OpenArm-Based Laboratory Mobile Manipulation

arXiv:2608.07154v1 Announce Type: cross Abstract: Open-source robotics and foundation models have lowered the barrier to embodied AI, yet language-guided laboratory automation still requires reliable

safetyarxiv-cs-ai

RoRA: Role-Oriented Regional Allocation for Visual Token Pruning in MLLMs

arXiv:2608.07088v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) encode images as long visual token sequences, making prefilling and KV-cache storage expensive. Existing trai

Simple-OPD: Demystifying Warm-up for On-policy Distillation

arXiv:2608.06802v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own rollouts with token-level supervision from teacher models, but its effectiveness can depend str

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling

arXiv:2608.07222v1 Announce Type: new Abstract: Neural scaling laws are foundational for language model development, yet standard formulations systematically under- and overestimate loss at data-scarc

researcharxiv-cs-cl

Suppress and Diversify: Refining Robust Pathways for Corruption Robustness

arXiv:2608.06712v1 Announce Type: new Abstract: Model robustness against natural image corruptions is essential for safety-critical applications. While existing methods primarily focus on implicit rep

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family

arXiv:2608.07051v1 Announce Type: new Abstract: Generic parameter-efficient fine-tuning (PEFT) methods transferred from language models can fail silently on real-time detectors, whose heterogeneous op

DeepSeek-V4-Flash-0731 Q8_K_XL sometimes stops mid-task in OpenCode - anyone else seeing this?

Hey everyone, I've been experimenting with the new DeepSeek-V4-Flash-0731 release locally using the Unsloth Studio Q8_K_XL GGUF with OpenCode. Overall, it's been working really well, but I've noticed

9 Aug 2026

enabling PCI-E p2p for consumer Nvidia cards will yield you more than you think

Disclaimer - no LLM was used to write this post/note As larger post about my setup will come later, want to give heads-up to folks who use VLLM and >= 2 GPUs. So I have pretty meaty server (8 channel

8 Aug 2026

Qwen3.6 27B + 35B on vLLM, single R9700 (gfx1201)

I've been tuning my new Radeon AI Pro R9700, and figured that this would be useful information for people who are trying to optimise their setups. I'm pretty happy with these results and looking forwa

8 Aug 2026

A Paragraph is Worth a Thousand Captions: Rethinking Text Supervision for Vision-Language Retrieval

arXiv:2608.05260v1 Announce Type: new Abstract: Contrastive vision-language models such as CLIP and BLIP are typically trained on short image captions, limiting their ability to retrieve images from d

Audio-to-Score Transcription using Pre-trained Features, Data Augmentation, and the New SheetSage-A2S Dataset

arXiv:2608.06165v1 Announce Type: cross Abstract: Existing audio-to-score (A2S) systems primarily focus on classical music, and the application to popular music remains underexplored. This paper first

Benchmarking and Enhancing LLMs for Rule-Intensive Review of National Standard Documents

arXiv:2608.06312v1 Announce Type: new Abstract: Large language models (LLMs) increasingly support complex professional tasks, yet their capabilities in rule-intensive document review remain insufficie

Beyond Flat Policies: Hierarchical Post-Training for Embodied Agents in Robotic Manipulation

arXiv:2608.05999v1 Announce Type: new Abstract: Vision-language-action (VLA) models have demonstrated remarkable capabilities in robotic manipulation by leveraging pretrained vision-language models. H

researcharxiv-cs-ro

ChronoVision: Temporal Reasoning via Latent State Reconstruction

arXiv:2608.05631v1 Announce Type: new Abstract: Multimodal large language models excel at passive perception but struggle with complex visual cognitive tasks requiring multi-step temporal reasoning. T

CNM-BERT: A Drop-In Structural Embedding for Chinese Characters via Ideographic Description Sequences

arXiv:2608.05167v1 Announce Type: new Abstract: Token-based encoders like BERT treat Chinese characters as atomic identifiers, ignoring their recursive orthographic structure. Consequently, models rel

DASH: Decoupled Adaptive Surrogate - Acquisition Harness for Automated Bayesian Optimization

arXiv:2608.00641v2 Announce Type: replace Abstract: Bayesian optimization (BO) relies on a surrogate model and an acquisition function, yet the most suitable choices vary across tasks and optimization

Domain-Grounded Candidate Selection for Agentic Image Editing: A Shadow Removal Case

arXiv:2608.06075v1 Announce Type: cross Abstract: Commercial vision-language models are reshaping computer vision, with visual priors broad enough to rival task-specific systems. This raises a natural

DREAM: LLM-based Dynamic Role-playing via Event-Aware Memory Graph

arXiv:2608.05170v1 Announce Type: cross Abstract: Role-playing agents (RPAs) have emerged as a key application of large language models, enabling immersive and high-fidelity character simulation. Accu

Energy-Guided Flow Matching

arXiv:2608.05811v1 Announce Type: new Abstract: Pixel-space generative models bypass lossy latent compression, yet necessitate joint learning of global structure and fine-grained details in a high-dim

EschaLabs/Qwen3.6-35B-A3B-Escha-W2 · Hugging Face

Hey peeps. I know you're tired of low quants giving hard to believe numbers. I'm quite skeptical too and from what I tried I'm often left with the impression that the claims fall short. So this model

Evidential Rule Learning for Interpretable Classification with Abstention

arXiv:2608.05859v1 Announce Type: cross Abstract: Interpretable classification often requires more than accurate predictions for real-life deployment: models should be transparent about the evidence b

GST-Bench: Can VLMs Develop Global Spatial Awareness from Video?

arXiv:2608.05747v1 Announce Type: new Abstract: Spatial intelligence is fundamental to embodied agents, yet existing benchmarks focus on local spatial perception from single or few viewpoints, overloo

HarnessOpt-Bench: Evaluating LLMs at Harness Optimization

arXiv:2608.06301v1 Announce Type: new Abstract: As LLMs are increasingly deployed within agentic systems, their capabilities depend not only on the model weights but also on the harness: the prompts,

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging

arXiv:2608.05541v1 Announce Type: new Abstract: Evolution Strategy (ES) is a promising alternative to gradient-based fine-tuning for resource-constrained Large Language Model (LLM) reasoning. However,

Innocent Panels, Hateful Stories: Evaluating and Detecting Hateful Intent in Multi-Turn Visual Story Generation

arXiv:2608.05210v1 Announce Type: cross Abstract: Picture books and comics have long been used to disseminate hateful narratives because they are easily understood even by children, as exemplified by

IPV-Bench: Benchmarking Image Protection Methods under Diverse Image-to-Video Generation Scenarios

arXiv:2603.26154v2 Announce Type: replace Abstract: Image-to-video (I2V) generation models can be misused to animate a single image into a convincing fake video, motivating perturbation-based image pr

MoCA: Implicit Social Context Analysis

arXiv:2608.05825v1 Announce Type: new Abstract: Human social communication, such as affection and intent, is often conveyed in highly implicit ways, where underlying meanings are expressed through ind

NeSy-RAG: Neuro-Symbolic RAG for Explainable Question Answering

arXiv:2608.06292v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves question answering by grounding large language models (LLMs) in external knowledge such as text corpora. H

Applications

nnMIL: A generalizable multiple instance learning framework for computational pathology

arXiv:2511.14907v2 Announce Type: replace Abstract: Computational pathology holds substantial promise for improving diagnosis and guiding treatment decisions. Recent pathology foundation models enable

applicationsarxiv-cs-cv

PoolBench: A Benchmark for Pooling Strategies in Concept Representation Evaluation for Decoder-Only LLMs

arXiv:2608.05162v1 Announce Type: new Abstract: Pooling is a consequential but under-examined design choice in decoder-only concept representation work: practitioners must collapse token-level hidden

Robust Native Language Identification through Agentic Decomposition

arXiv:2509.16666v2 Announce Type: replace Abstract: Large language models (LLMs) often achieve high performance in native language identification (NLI) benchmarks by leveraging superficial contextual

Schema-Guided Hierarchical Information Extraction and Semantic Evaluation Using Generative AI

arXiv:2608.06167v1 Announce Type: new Abstract: We present a schema-based framework for extracting complex, structured information from unstructured text documents using generative AI, followed by aut

Task-Conditional Flow Matching for Balanced Multilingual Text Embedding Adaptation

arXiv:2608.05785v1 Announce Type: cross Abstract: Multilingual text embedding models are commonly adapted using a single training objective across diverse tasks, despite different tasks requiring fund

Unifying Structured and Unstructured Data Insights with BQ Search Innovations

model-releasesgoogle-cloud-ai

Modern enterprises possess a vast amount of unstructured data, yet they frequently encounter significant challenges in managing and extracting value from it. Historically, unlocking the insights hidde

Advancing Utility Pole and Sign Detection Through Deep Learning

arXiv:2608.04061v1 Announce Type: new Abstract: Utility poles are an essential part of the infrastructure used to support power distribution systems and other critical public services. Their regular i

An active-learning framework for real-time depth perception from monocular vision streams

arXiv:2608.04917v1 Announce Type: new Abstract: Biological visual systems can perceive depth from monocular vision flow, continuously integrating temporal visual cues while maintaining a balance betwe

Anthropic will design its own hardware to power Claude

model-releasesars-technica

Anthropic is hiring a custom silicon team to design proprietary chips that will power its Claude models, while still planning a multi‑chip strategy that mixes internally designed hardware with compone

Anyone understand what the equivalent of GPT-5.6 Instant in ChatGPT is for the OpenAI API?

model-releasessimon-willison--x

The tweet is a question from user Simon Willison (posted on 6 Aug 2026) asking which OpenAI API model corresponds to the ChatGPT “GPT‑5.6 Instant” version. No answer or clarification is included in th

Local Ai

Bi-Level Reinforcement Learning Pathway for Sim-to-Real Optimality

arXiv:2510.17709v2 Announce Type: replace-cross Abstract: Training Reinforcement Learning (RL) policies using simulation models before deployment in real-world environments is a common strategy when r

local-aiarxiv-cs-ai

BIM-Native Tokenization for Constraint-Aware Room Layout Synthesis

arXiv:2512.04832v3 Announce Type: replace Abstract: We present a BIM-native tokenization for room-level layout synthesis in Building Information Modeling (BIM) scenes. The core contribution is represe

COMPAS: Difficulty-Aware Joint Search for Optimizing Code Generation

arXiv:2608.04336v1 Announce Type: cross Abstract: Code generation systems make each LLM call with a model, a prompt, and decoding settings. However, existing optimization methods usually tune only par

researcharxiv-cs-ai

Elbow-Based MoE Routing: A Training-Free Inference Time Plugin for Expert Selection

arXiv:2608.04401v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models enable model scaling while maintaining low inference-time compute by activating only a subset of experts per token. Howe

researcharxiv-cs-lg

ExeCRE: Execution-Consistency Guided Reliability Estimation for Self-Correcting Code Generation

arXiv:2608.04439v1 Announce Type: cross Abstract: Large language models (LLMs) have made notable progress in code generation, but they still struggle on challenging tasks that require sophisticated al