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QCell: Recombining and Aligning Cell Queries for Overlapping Instance Segmentation

arXiv:2608.29253v1 Announce Type: cross Abstract: Instance segmentation of overlapping cells in microscopy remains challenging due to semi-transparent structures that produce weak boundaries and mixed

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Model Releases

Qdrant Builds a 10-Billion-Document Vector Search Benchmark Dataset on Vultr

DGX agent

Qdrant has released **Qdrant‑Fineweb‑10B**, a public benchmark dataset comprising dense and sparse embeddings for 10 billion documents from the FineWeb corpus and exact results for 120,000 queries to

model-releasesvultr

1 Sept 2026

QQ: A Language Metadata Toolkit for Multilingual NLP

arXiv:2603.00620v3 Announce Type: replace Abstract: Multilingual NLP research increasingly involves hundreds or thousands of languages across different datasets. Managing, discovering, and reporting l

Quantifying and Mitigating Korean Jamo-Level Typographical Vulnerabilities in Large Language Models

arXiv:2608.30229v1 Announce Type: new Abstract: Korean introduces an additional typographical perturbation level not captured by ordinary character-level edit models: because syllable blocks are inter

Quantifying Error Tolerance in Synthetic Data: An Atomic-level Operand vs. Operator Perturbation Study

arXiv:2608.29144v1 Announce Type: new Abstract: Synthetic data generation has become a cornerstone for advancing large language models. However, the lack of the quantitative analysis for error toleran

Agents

Quantitative Evidence Mining for Plausibility-Aware Biomedical AI

arXiv:2608.30393v1 Announce Type: new Abstract: Biomedical artificial intelligence (AI) systems increasingly extract, organize, and reuse scientific claims from literature, clinical trials, and regula

agentsarxiv-cs-cl

Quantitative Target Convergence and Uniform-in-Time Propagation of Chaos for Langevin-Regularized SVGD

arXiv:2608.28827v1 Announce Type: cross Abstract: We establish quantitative convergence to the target and uniform-in-time propagation of chaos for Langevin-regularized Stein variational gradient desce

Quantum-Grassmann-Plucker Token Mixing for Deep Learning-Based Post-Disaster Damage Assessment

arXiv:2608.30633v1 Announce Type: new Abstract: Timely post-disaster building damage assessment from satellite imagery is a critical engineering decision support task, yet it remains constrained by cl

Question: Why is prefill unbelievably faster in vLLM than other inference engines?

model-releasesr-localllama

I only started using some vLLM forks recently in a 4 x 48GB 4090 system. DS4F - ~5000pp/180tg (DSpark) Qwen3.8 Flash next - ~7500pp/135tg (MTP) This is amazing, like having the API in my house. But it

Qwen 3.8 27b (Q4KM) oneshot a Super Mario clone

model-releasesr-localllama

I am absolutely blown away. Yes my setup is crap but the fact that it managed to do this in a single take is unbelievable (and I'm a developer). Hardware used: - Windows PC with 4070ti (12GB VRAM, 32G

qwen4exp fixes in llama.cpp

model-releasesr-localllama

if you are on Qwen Flash Next make sure to update your build often https://preview.redd.it/zoq3j9gnjvmh1.jpg?width=900&format=pjpg&auto=webp&s=bb21bc405696df94fd5ce38c22f4ca6dc596135f merged already (

R^2A: Learning Persona Policies Through Persona Representation Learning and Runtime Alignment

arXiv:2608.29798v1 Announce Type: cross Abstract: The same Persona behavior can be beneficial in one context but harmful in another, causing static Persona elicitation to perform inconsistently across

Agents

RACER: Reinforced Agent Collaboration for Explainable Reasoning on Knowledge Graphs

arXiv:2608.29263v1 Announce Type: new Abstract: Large Language Models (LLMs) often suffer from hallucination and struggle with complex reasoning tasks requiring multi-hop domain knowledge. While integ

agentsarxiv-cs-ai

Rad-R: A Raw-ADC Radar Dataset and Capture-Invariant SSM for Hardware-Fault Diagnosis

model-releasesarxiv-cs-cv

arXiv:2608.30896v1 Announce Type: new Abstract: Automotive mmWave radar can develop vibration, antenna misalignment, radome blockage, and receive-channel degradation that corrupt the signal before per

RAGDiffusion++: From Macro-Retrieval to Micro-Fidelity Alignment for Garment Generation

arXiv:2608.29280v1 Announce Type: cross Abstract: Standard clothing asset generation---restoring forward-facing flat-lay garment images from diverse real-world contexts---holds immense commercial valu

RailGen: Improving Railway Intrusion Detection via Agent-Guided Small-Scale Foreign Object Generation

arXiv:2608.30727v1 Announce Type: cross Abstract: Small-object detection under long-tailed data distributions is a fundamental yet challenging problem in multimedia. Railway Foreign Object Detection (

Agents

RailSyn: Diagnosis-Guided Image Generation for Traceable Data Completion in Railway Foreign Object Detection

arXiv:2608.30709v1 Announce Type: cross Abstract: Railway foreign object detection (RFOD) is critical to safe railway operation, yet scarce real positive samples incompletely represent task-relevant v

agentsarxiv-cs-ai

Randomized YaRN Improves Length Generalization for Long-Context Reasoning

arXiv:2606.23687v2 Announce Type: replace Abstract: Large language models (LLMs) are typically pretrained on short sequences and then extended to work on longer sequences with additional training. How

RankShift: In-Database Detection and Explanation of Categorical Shifts

arXiv:2608.28922v1 Announce Type: new Abstract: A login service can receive its usual number of failed sign-ins while one source grows from 2% to 30% of them. The same pattern appears in system logs w

Rate-Coding Bundle Memory: A Unified Model of Memory and Control for Symbolic Computation in the Brain

arXiv:2608.29189v1 Announce Type: cross Abstract: We propose a neurobiologically plausible model of cognition that combines the advantages of connectionist and symbolic systems, and that can explain a

researcharxiv-cs-ai

Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning

arXiv:2401.15719v5 Announce Type: replace-cross Abstract: We prove a non-asymptotic central limit theorem for vector-valued martingale differences using Stein's method, and use Poisson's equation to e

Reachability-Based Capability Confinement for LLM Agents under Indirect Prompt Injection

arXiv:2608.30041v1 Announce Type: cross Abstract: Large language model agents place outputs from external skills into their execution context, allowing attacker-controlled data to influence later priv

Reactivating Test-Time Scaling for Plane Geometry Problem Solving

arXiv:2608.30156v1 Announce Type: new Abstract: Plane geometry problem (PGP) solving has become a critical benchmark for multimodal reasoning because it requires accurate visual perception and precise

Read the Room, Read the Image: Understanding Indirect Speech Acts in Multimodal Visual Contexts

arXiv:2608.30270v1 Announce Type: new Abstract: Indirect speech acts (ISAs) require pragmatic reasoning over context, as directive intent can- not be inferred from surface form alone. Prior text-based

Reading the News: Adapting Large Language Models to Swedish Journalism Through Continued Pre-Training

arXiv:2608.30609v1 Announce Type: cross Abstract: Large language models are increasingly capable in general, but their utility can remain modest in niche or understudied areas. One approach to address

Real-Time Deadlines Reveal Fragile Temporal Adaptation in LLM Strategic Dialogues

arXiv:2601.13206v2 Announce Type: replace Abstract: Large Language Models (LLMs) generate text token-by-token in discrete time, yet real-world communication, from therapy sessions to business negotiat

Local Ai

Real-Time Scene-Adaptive Tone Mapping for High-Dynamic Range Object Detection

arXiv:2608.30400v1 Announce Type: new Abstract: High-dynamic-range (HDR) images, with their rich tone and detail reproduction, hold significant potential to enhance computer vision systems, particular

local-aiarxiv-cs-cv

Hardware

Real-Time Video Anomaly Detection Using YOLO Pose Estimation and CLIP-Based Semantic Scoring

arXiv:2608.31074v1 Announce Type: cross Abstract: We propose a lightweight two-stage framework for real-time video anomaly detection. The first stage employs YOLO v11n-pose to detect persons and extra

hardwarearxiv-cs-ai

RealCAD: Towards Real-World Image-to-CAD Reconstruction under Domain Shift and Parameter Bias

model-releasesarxiv-cs-cv

arXiv:2608.30617v1 Announce Type: new Abstract: Reconstructing editable Computer-Aided Design (CAD) models from images is essential for downstream modification, manufacturing, and design reuse. Howeve

RealOOB: A Definition-Consistent Real-World Oriented Occlusion Boundary Benchmark

model-releasesarxiv-cs-cv

arXiv:2608.30820v1 Announce Type: new Abstract: Occlusion boundaries (OBs) are pixel-level image boundaries corresponding to surface visibility discontinuities caused by occlusion. Through precise bou

Reasoning Beyond Language: A Comprehensive Survey on Latent Chain-of-Thought Reasoning

arXiv:2505.16782v3 Announce Type: replace Abstract: Large Language Models (LLMs) have shown impressive performance on complex tasks through Chain-of-Thought (CoT) reasoning. However, conventional CoT

Reciprocity Separates Gradient Flow from Rotation in Conservative Physical Learning

arXiv:2608.30778v1 Announce Type: new Abstract: Physical learning lets a trainable material or network use its own physical response to carry error signals, reducing the need for a separately programm

Recognition-Refusal Misalignment in LLMs: Why Models Answer Structurally Unanswerable Questions

arXiv:2608.29109v1 Announce Type: new Abstract: Large language models often answer structurally unanswerable questions, such as computing cot(-540{eg}) or evaluating (1).startswith('1'), instead of ab

safetyarxiv-cs-cl

Reconciling Process Supervision with Outcome-Based Credit in Agentic Policy Optimization

arXiv:2608.31077v1 Announce Type: new Abstract: Outcome-based reinforcement learning provides verified feedback for language-model agents, but assigns trajectory-level advantage uniformly to all decis

Applications

ReconSplat: Generalizable 3D Scene Reconstruction Beyond Observed Views

arXiv:2608.28895v1 Announce Type: new Abstract: We introduce ReconSplat, a feed-forward model for 3D scene reconstruction that aims to address the longstanding trade-off between plausible view generat

applicationsarxiv-cs-cv

Reconstruction-Aware Cryo-EM Particle Picking

arXiv:2608.28838v1 Announce Type: cross Abstract: Cryo-electron microscopy (cryo-EM) determines the structures of proteins and macromolecular assemblies at near-atomic resolution, and the final 3D rec

Rectification Reimagined: A Unified Mamba Model for Image Correction and Rectangling with Prompts

arXiv:2512.18718v3 Announce Type: replace Abstract: Image correction and rectangling are valuable tasks in practical photography systems such as smartphones. Recent remarkable advancements in deep lea

Redesigning and Auditing Deep Research Writing for Faithful Reports

arXiv:2608.28643v1 Announce Type: cross Abstract: Rubric-based evaluations of deep-research (DR) systems often obscure fine-grained factual failures in generated reports. We introduce CLAIMPROBE, a cl

researcharxiv-cs-ai

RedLight-VLA: Models for traffic-rule grounding and behavioral emphasis in driving policies

arXiv:2608.28656v1 Announce Type: cross Abstract: Behavior-cloned Vision-Language-Action (VLA) driving policies struggle with rare rule-governed maneuvers at signalized intersections. Braking and laun

REER-PT: Reverse-Engineered Reasoning for Perplexity-Guided Pre-training Data Augmentation

arXiv:2608.30627v1 Announce Type: new Abstract: As language-model compute continues to scale, high-quality training data is becoming an increasingly important bottleneck. Conventional next-token predi

Reference-Grafting Matches Fine-Tuning at Eliciting Sandbagged Capabilities

arXiv:2608.29458v1 Announce Type: cross Abstract: Sandbagging, in which a model deliberately underperforms on an evaluation despite retaining the underlying capability, threatens the safety evaluation

RegDivergence-101: An LLM Benchmark for Cross-Jurisdiction Regulatory Contradiction Detection in Life Sciences

arXiv:2608.28607v1 Announce Type: new Abstract: Pharmaceutical sponsors developing a drug for both the United States and the European Union must reconcile guidance issued independently by the FDA and

Applications

RegionCache: Semantic-Aware Region Reuse for Efficient Multi-Turn Image Generation

arXiv:2608.29809v1 Announce Type: new Abstract: Real-world image generation often involves multi-turn editing, where users iteratively modify small regions while most image content remains unchanged.

applicationsarxiv-cs-cv

RegionFM: Interpretable Region-Based Brain MRI Classification Using Foundation Model Embeddings

arXiv:2607.16325v2 Announce Type: replace Abstract: Foundation models provide powerful representations for brain MRI analysis, but their predictions remain difficult to interpret in anatomically meani

ReGraP-LLaVA: Reasoning enabled Graph-based Personalized Large Language and Vision Assistant

arXiv:2505.03654v3 Announce Type: replace-cross Abstract: Multimodal Large Language Models have shown strong performance across multimodal tasks, and recent personalized MLLMs can recognize user-speci

REIGN: Refurbished Embeddings with Integrated Guidance Networks for Efficient Context-Length Scaling

arXiv:2608.29899v1 Announce Type: cross Abstract: Dense retrieval over long documents is expensive. Token-level encoders scale quadratically in sequence length, and most long-context embedding models

Reinforcement Learning for Symbolic Equation Solving

arXiv:2608.30162v1 Announce Type: new Abstract: We present a reinforcement-learning agent that solves symbolic equations step by step, covering both nonlinear closed equations (radicals, exponentials,

safetyarxiv-cs-lg

Reliable Benchmarking of Artifact Detection in Computational Pathology: A Reproducibility and Uncertainty Analysis

arXiv:2608.30835v1 Announce Type: cross Abstract: Background and Objective: Quality control is a prerequisite for whole-slide image analysis, yet the benchmarks on which quality-control methods are co

researcharxiv-cs-ai