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Post Fusion Bird's Eye View Feature Stabilization for Robust Multimodal 3D Detection

arXiv:2603.05623v2 Announce Type: replace-cross Abstract: Camera-LiDAR fusion is widely used in autonomous driving to enable accurate 3D object detection. However, bird's-eye view (BEV) fusion detecto

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Tutorials

Predicting Spatiotemporal Mobile Sensing-Based PM2.5 Concentrations Using Low-Rank Adapted Spatially Attentive Graph Neural Network

DGX agent

arXiv:2609.04693v1 Announce Type: new Abstract: Urban air quality can vary significantly along transit corridors, necessitating high-resolution monitoring. This work introduces a novel mobile-sensing

tutorialsarxiv-cs-ai

7 Sept 2026

PRICE: A Systematic Study of LLM Adaptation Choices for Bitcoin Price Forecasting

arXiv:2609.05235v1 Announce Type: cross Abstract: Cryptocurrency markets exhibit extreme volatility and non-stationary dynamics that challenge conventional forecasting methods. Although Large Language

PRISM-Bench: An Audio-Centric Diagnostic Benchmark for Text-to-Audio-Video Generation

arXiv:2609.04867v1 Announce Type: cross Abstract: Text-to-audio-video (T2AV) generation has advanced rapidly, but its evaluation still underestimates the audio modality. Existing benchmarks either tre

Local Ai

Privacy Failure in Split-LLM Training, The Returned Gradient Nullifies the Decoys

arXiv:2609.04382v1 Announce Type: cross Abstract: We present a systems-security case study of a two-node split-LLM training system whose privacy evaluation passed while leaving an observable channel u

local-aiarxiv-cs-lg

ProCA: Progressive Contrastive Alignment for Robust EEG Visual Decoding

arXiv:2609.05094v1 Announce Type: new Abstract: Electroencephalogram (EEG) visual decoding aims to recover visual semantics from non-invasive neural time-series signals, for which robust alignment bet

PROMPT2BOX:Improving LLM Weakness Discovery and Specificity Estimation by Uncovering Entailment Structure among Prompts

arXiv:2603.21438v3 Announce Type: replace Abstract: To discover the weaknesses of LLMs, researchers often embed prompts into a vector space and cluster them to extract insightful patterns. However, ve

researcharxiv-cs-cl

ProtLingo: Efficient Protein Language Modeling via Conditional Memory and Expert Routing

arXiv:2609.04793v1 Announce Type: new Abstract: Proteins perform diverse cellular functions, and even single amino-acid substitutions can alter stability, activity, or molecular interactions. Protein

ProToMEx: Rapid, Interpretable Explanations via Structured Representations

arXiv:2609.04265v1 Announce Type: new Abstract: Existing post-hoc explainers for machine learning classifiers primarily focus on feature attribution, assigning importance scores to individual features

Proton Irradiation Characterization of an Open-Source ML Accelerator on a Zynq UltraScale+ MPSoC

arXiv:2609.05249v1 Announce Type: cross Abstract: As spaceborne computing systems increasingly rely on neural network (NN) accelerators, the opacity of commercial, black-box architectures severely res

PuTR-CouT: Counting-by-Tracking in Camera-Trap Image Sequences

model-releasesarxiv-cs-cv

arXiv:2609.05038v1 Announce Type: new Abstract: Species identification in camera trap images has been widely studied, but key ecological modeling tasks such as species abundance or density estimation

Qlippy: A Retrieval-Augmented GenAI Assistant for Reproducible Quantum Workflows and Experiment Tracking

arXiv:2609.05039v1 Announce Type: cross Abstract: Quantum software development is iterative and error-prone. Noisy hardware and repeated re-execution make experiment tracking, provenance, and reproduc

QoNext: Towards Next-generation QoE for Foundation Models

arXiv:2509.21889v3 Announce Type: replace Abstract: Existing evaluations of foundation models predominantly focus on output correctness, treating interaction as a static exchange of information. Howev

researcharxiv-cs-cl

Quality-diversity in dissimilarity spaces

arXiv:2211.12337v4 Announce Type: replace Abstract: The theory of magnitude provides a mathematical framework for quantifying and maximizing diversity. We apply this framework to formulate quality-div

Quality Recovery for Quantized KV Caches via Low-Rank Attention Adaptation

model-releasesarxiv-cs-cl

arXiv:2609.04263v1 Announce Type: cross Abstract: Low-bit key--value (KV) caches reduce the memory required for autoregressive decoding, but the resulting quality loss depends on the model and quantiz

Quantum-Assisted Memory-Efficient Training for Parameter-Intensive Wi-Fi-Based Human Activity Recognition

model-releasesarxiv-cs-lg

arXiv:2609.04271v1 Announce Type: new Abstract: Wi-Fi-based human activity recognition (HAR) has become an important part of integrated sensing and communications, paving the way for a range of contex

Tools

Quoting Jakub Pachocki

The strongest argument I see for continuing to train much smarter models quickly is the need to build defensive systems against the dangers posed by other AI. [...] We will need powerful, aligned AI f

toolssimon-willison

Qwen 3.8 27B run just 0.7tok/s on 5060ti 16GB

I just tried to run Qwen 3.8 27B 4bit qwant on 5060ti 16GB and got terrible results. With Qwen 3.6 I got something around 15-20 tok/s. Are there any combination of parameters or tweeks how to push the

model-releasesr-ollama

Qwen 3.8 Next Flash is really really REALLY verbose..

model-releasesr-localllama

Long time user of 3.6 27b, switched over to Next Flash since it's a logical step up even from 3.8 27b. It's soooo verbose, i'm talking 13 minutes of thinking time on single turn coding requests at app

Qwen3.5 0.8B on CPU

model-releasesr-localllama

Since the Qwen3.5 0.8B model is an interesting one for small specialized fine tunes, I was curious how fast it can run on CPUs. Why CPUs? Mainly because I want to use it as a local dictation cleanup m

Qwen3.8-27B on M1 Max 32GB: MLX 15.8 tok/s vs llama.cpp 9.7 tok/s - but llama.cpp prefill is faster

I’ve been setting up an M1 Max Mac Studio (24-core GPU, 32GB unified memory) as a local LLM server and wanted to compare MLX vs llama.cpp on Qwen3.8-27B. I tried to keep the model footprint and benchm

model-releasesr-ollama

Radeon RX 7900 GRE 16GB and RX 480 8GB Vulkan benchmarks llama.cpp

model-releasesr-localllama

My XFX Radeon RX 7900 GRE 16GB Vram GPU struggles with models over 20B size. I added my Radeon RX 480 8GB Vram GPU to the system and ran a few benchmarks using llama.cpp Ubuntu Vulkan build 10453. htt

ReaDiT Guidance: Control for Image and Video Generation using Diffusion Transformer Features

arXiv:2609.04649v1 Announce Type: new Abstract: We present DiT Readout (ReaDiT) Guidance, a lightweight framework for controlling generation with Diffusion Transformer (DiT) models via their internal

researcharxiv-cs-cv

Real-World Multi-Modal and Longitudinal Lung Cancer Dataset

model-releasesarxiv-cs-cv

arXiv:2609.05202v1 Announce Type: cross Abstract: Multi-modal learning has demonstrated strong potential in medical applications by integrating heterogeneous data sources such as medical imaging, clin

Really strong benchmark paper on coding agents. Claude Opus 5 running under Claude Code passes 23.9% of the evaluations. An expert human ref…

Really strong benchmark paper on coding agents. Claude Opus 5 running under Claude Code passes 23.9% of the evaluations. An expert human reference scores 82.2%. Here is what the task actually is. The

model-releasesdair-ai--x

Reasoning Without Inference Cost: Latent Semantic Scaffolding for Robot VLA Policies

arXiv:2609.04893v1 Announce Type: new Abstract: Vision-language-action (VLA) models are trained by imitation and capture what action to take but not why; adding causal reasoning improves manipulation,

safetyarxiv-cs-ro

ReCAST: Restoration-aware Cascaded Stage-wise Training for Obfuscated SMS Risk Classification

arXiv:2609.04878v1 Announce Type: cross Abstract: Fraudulent messages sent via Short Message Service (SMS) are increasingly obfuscated to evade cost-conscious classifiers in production systems. In Chi

Recovering molecules from coarse-grained beads: free-energy-conditioned generative backmapping across chemical space

arXiv:2609.04432v1 Announce Type: cross Abstract: Transferable coarse-grained (CG) force fields compress chemical space: by aggregating atoms into a reduced set of interaction beads, models such as MA

Recurrence Is Not Enough: Causally Validating Multilingual SAE Translation Features in Gemma 2 and 3

arXiv:2609.04808v1 Announce Type: cross Abstract: Sparse autoencoder (SAE) features are increasingly used to explain and steer language-model behavior, but it remains unclear whether a feature found i

Reducing Hallucinated Transcripts in Whisper via Hallucination Space Projection

arXiv:2609.04561v1 Announce Type: new Abstract: Whisper is a widely used foundation model for automatic speech recognition (ASR), but its generative decoder can produce fluent hallucinated transcripts

Agents

RefactorPlatform: An Open-Source Harness for Controlled Evaluation of Repository-Scale Refactoring Agents

arXiv:2609.04898v1 Announce Type: cross Abstract: Repository-scale refactoring requires coding agents to propagate a single change across many interdependent files without altering program behavior, y

agentsarxiv-cs-ai

Local Ai

RefDiT: Local Attribute Guidance in Reference-Based Image Generation

arXiv:2609.04976v1 Announce Type: new Abstract: Personalization models generate new images guided by a few subject references, while style transfer methods aim to produce images aligned with a global

local-aiarxiv-cs-cv

REFINE: LLM Refinement over Budgeted Text-Attributed Graphs for Personalized Medical Concept Representation

arXiv:2609.04415v1 Announce Type: cross Abstract: Learning rich medical concept representations is essential for EHR prediction. Text-attributed knowledge graphs (TKGs) provide a natural foundation by

Reflection-aware Generative Novel View Synthesis

arXiv:2609.05382v1 Announce Type: cross Abstract: We propose Ref-GeNVS, a training-free, reflection-aware method for generative novel view synthesis (NVS) in mirror scenes. Existing multi-view diffusi

Refuse without Refusal: A Structural Analysis of Safety-Tuning Responses for Reducing False Refusals in Language Models

arXiv:2609.04714v1 Announce Type: cross Abstract: Striking a balance between helpfulness and safety remains a fundamental challenge in aligning large language models. To achieve this balance, models s

RegionFed: Federated Learning for Personalized Query Understanding in Heterogeneous Retail Environments

arXiv:2609.05403v1 Announce Type: cross Abstract: Retail search systems serve diverse geographic regions with distinct query patterns, vocabularies, and product preferences, creating significant data

Regularity of Second-Order Elliptic PDEs in Spectral Barron Spaces

arXiv:2602.19381v2 Announce Type: replace-cross Abstract: We establish a regularity theorem for second-order elliptic PDEs on R^{d} in spectral Barron spaces. Under mild ellipticity and smallness assu

Reinforcement Learning for improving Large Language Models' Catalan text simplification capabilities

arXiv:2609.04823v1 Announce Type: cross Abstract: Although automatic text simplification (ATS) is critical for accessibility, its progress has not matched the rapid evolution of broader natural langua

Reinforcement Learning for Sequential Solar PV Policy Design under Uncertainty: An Agent-Based Approach

arXiv:2609.04880v1 Announce Type: new Abstract: Designing effective and fiscally sustainable policies for solar photovoltaic (PV) adoption requires balancing adoption gains against public expenditure

Repeat-After-Me: Black-Box Adaptive Visual Prompt Injection

arXiv:2609.04533v1 Announce Type: cross Abstract: Prompt injection is widely recognized as a major security threat to AI agents that interact with untrusted external data, such as websites, documents,

Repeated Queries Exhaust an LLM's Brand Recommendations but Not Its Sources

arXiv:2609.05059v1 Announce Type: cross Abstract: Whether repeated identical buying questions exhaust a language model's brand recommendations depends on retrieval. Across 300 question-engine cells (5

researcharxiv-cs-cl

Applications

Replit is officially in London. 🇬🇧 As we open our first international office here today, we’re honored to mark this important milestone wi…

Replit is officially in London. 🇬🇧 As we open our first international office here today, we’re honored to mark this important milestone with @MayorofLondon, Sadiq Khan and his team, His Majesty’s Gove

applicationsreplit--x

Representation Redundancy and Structural Complexity in Finite-Field Inversion

arXiv:2609.04583v1 Announce Type: new Abstract: The representation chosen for a mathematical operation can affect both its algebraic form and its empirical learning difficulty. We study this phenomeno

Reservoir-Based Graph Convolutional Networks

model-releasesarxiv-cs-cv

arXiv:2603.24131v2 Announce Type: replace-cross Abstract: Message passing is a core mechanism in Graph Neural Networks (GNNs), enabling the iterative update of node embeddings by aggregating informati

Resilience Beyond Stationary Client Unavailability: Unlocking Efficient and Unbiased Federated Learning

model-releasesarxiv-cs-lg

arXiv:2609.04763v1 Announce Type: new Abstract: Due to resource constraints or external and internal uncertainties, clients in real-world federated learning systems are often intermittently available

ResLearn-XR: Residual Learning for Network Traffic and Quality-of-Experience-Aware Modeling in Extended Reality

arXiv:2609.04493v1 Announce Type: new Abstract: We present ResLearn-XR, a residual learning framework for predicting eXtended Reality (XR) network traffic and estimating Quality-of-Experience (QoE) ri

Agents

Rethinking Indirect Prompt Injection as a Test-Time Search Problem

arXiv:2609.04495v1 Announce Type: new Abstract: We formulate indirect prompt injection as a test-time search over a task-dependent attack surface induced by the environment, user task, and injection t

agentsarxiv-cs-ai

Retinal OCTA Phenotyping with LLM Reporting for Alzheimer's Disease

model-releasesarxiv-cs-cl

arXiv:2609.04689v1 Announce Type: cross Abstract: Early identification of Alzheimer's disease (AD) remains challenging because established assessment methods can be costly, resource-intensive, or unsu