Search: “models”

Automatic Contextual Audio Denoising

arXiv:2605.22262v1 Announce Type: cross Abstract: Audio context determines which sound components and sources are relevant and which can be perceived as irrelevant (noise) by listeners. For example, t

Tutorials

Benchmarking Machine Learning Architectures for Antimicrobial Stewardship in Pediatric ICUs

DGX agent

arXiv:2605.22611v1 Announce Type: new Abstract: Antimicrobial stewardship (AMS) is critical in pediatric intensive care units (PICUs), where diagnostic uncertainty often drives broad-spectrum antibiot

tutorialsarxiv-cs-lg

23 May 2026

Do Deep Ensembles Actually Capture Uncertainty in Graph Neural Networks?

arXiv:2605.22593v1 Announce Type: new Abstract: While deep ensembles are widely considered to be the default method for uncertainty quantification in deep learning, their effectiveness for graph-struc

Ex-GraphRAG: Interpretable Evidence Routing for Graph-Augmented LLMs

arXiv:2605.21994v1 Announce Type: new Abstract: GraphRAG conditions language models on subgraphs retrieved from knowledge graphs, encoded via message-passing GNNs. Because these encoders entangle node

From Snapshots to Trajectories: Learning Single-Cell Gene Expression Dynamics via Conditional Flow Matching

arXiv:2605.22340v1 Announce Type: new Abstract: Single-cell RNA sequencing (scRNA-seq) provides high-dimensional profiles of cellular states, enabling data-driven modeling of cellular dynamics over ti

safetyarxiv-cs-lg

Hybrid Kolmogorov-Arnold Network and XGBoost Framework for Week-Ahead Price Forecasting in Australia's National Electricity Market

arXiv:2605.22387v1 Announce Type: new Abstract: Accurate electricity price forecasting (EPF) is essential for market participants to support operational planning and risk management, yet remains chall

IKNO: Infinite-order Kernel Neural Operators

arXiv:2605.22182v1 Announce Type: new Abstract: Neural operators have achieved significant success in modern scientific computing due to their flexibility and strong generalization capabilities. Exist

Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approcimations

arXiv:2605.22557v1 Announce Type: new Abstract: We introduce an abstract neural flow framework for neural networks and neural operators. The framework contains two continuous-depth models, namely neur

On Statistical Estimation of Edge-Reinforced Random Walks

arXiv:2503.06115v2 Announce Type: replace-cross Abstract: Reinforced random walks (RRWs), including vertex-reinforced random walks (VRRWs) and edge-reinforced random walks (ERRWs), model random walks

One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs

arXiv:2605.22297v1 Announce Type: new Abstract: Learning rate configuration is a fundamental aspect of modern deep learning. The prevailing practice of applying a uniform learning rate across all laye

Protein Thoughts: Interpretable Reasoning with Tree of Thoughts and Embedding-Space Flow Matching for Protein-Protein Interaction Discovery

arXiv:2605.21522v1 Announce Type: cross Abstract: Protein-protein interactions (PPIs) govern nearly all cellular processes, yet computational methods for identifying binding partners typically produce

Representation Gap: Explaining the Unreasonable Effectiveness of Neural Networks from a Geometric Perspective

arXiv:2605.21692v1 Announce Type: new Abstract: Characterizing precisely the asymptotic generalization error of neural networks using parameters that can be estimated efficiently is a crucial problem

Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability

arXiv:2605.22142v1 Announce Type: new Abstract: Reinforcement learning under partial observability requires deciding what information to retain, yet most memory-based approaches do not explicitly mode

The case against me below is completely intellectually dishonest, filled with lies and misrepresentations, wrong about almost literally ever…

model-releasesgary-marcus--x

The case against me below is completely intellectually dishonest, filled with lies and misrepresentations, wrong about almost literally everything it says—a textbook example of propaganda: - I didn’t

The Neural Compiler: Program-to-Network Translation for Hybrid Scientific Machine Learning

arXiv:2605.22498v1 Announce Type: new Abstract: Scientific machine learning often requires combining known physics with unknown parameters or correction terms learned from data. Existing approaches ei

this has been my experience as well. there definitely were improvements, specifically wrt shell based computer use, but also regressions, es…

model-releasesjeremy-howard--x

this has been my experience as well. there definitely were improvements, specifically wrt shell based computer use, but also regressions, especially in the last 3 version bumps of flicker and gerperte

Towards Explainability of SLMs by investigating Token Level Activation

arXiv:2605.22377v1 Announce Type: new Abstract: Transformer-based language models such as BERT having 110M+ parameters have revolutionized natural language understanding, yet their internal mechanisms

When Are Teacher Tokens Reliable? Position-Weighted On-Policy Self-Distillation for Reasoning

arXiv:2605.21606v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a student on its own rollouts using a privileged teacher, but its standard objective weights all generated tok

3D LULC classification using multispectral LiDAR and deep learning: current and prospective schemes

arXiv:2605.22328v1 Announce Type: new Abstract: Land Use Land Cover (LULC) classification is essential for national 3D mapping, geospatial analysis, and sustainable planning. Multispectral (MS) LiDAR

A KL-regularization Framework for Learning to Plan with Adaptive Priors

arXiv:2510.04280v2 Announce Type: replace-cross Abstract: Effective exploration remains a central challenge in model-based reinforcement learning (MBRL), particularly in high-dimensional continuous co

safetyarxiv-cs-ro

A Task-Agnostic Algebraic Integrity Metric for Event-Camera Streams Toward SOTIF-Compliant Perception using Pearson Correlation Coefficient

arXiv:2605.21500v1 Announce Type: cross Abstract: Event cameras have emerged as a high-bandwidth, low-latency sensing modality for safety-critical perception in automated driving systems (ADS), offeri

Anthropic says Claude Mythos Preview has been used to find more than 10,000 high- or critical-severity vulnerabilities since the launch of Project Glasswing (Anthropic)

Anthropic: Anthropic says Claude Mythos Preview has been used to find more than 10,000 high- or critical-severity vulnerabilities since the launch of Project Glasswing — Last month, we launched Projec

model-releasestechmeme

Applications

AVI-HT: Adaptive Vision-IMU Fusion for 3D Hand Tracking

arXiv:2605.21714v1 Announce Type: new Abstract: We present AVI-HT, an adaptive visual-IMU fusion approach for tracking 3D hand poses by jointly modeling the egocentric image with on-glove 6-DoF IMU si

applicationsarxiv-cs-cv

ChronoMedKG: A Temporally-Grounded Biomedical Knowledge Graph and Benchmark for Clinical Reasoning

arXiv:2605.22734v1 Announce Type: new Abstract: Biomedical knowledge graphs (KGs) treat disease associations as static facts, but temporal information is crucial for clinical reasoning, e.g., a sympto

COCOTree: A Dataset and Benchmark for Open Tree-Structured Visual Decomposition

arXiv:2605.22068v1 Announce Type: new Abstract: We formalize and enable the task of open tree decomposition, which segments an image into hierarchical trees of visual components with unconstrained gra

Applications

Codec-Robust Attacks on Audio LLMs

arXiv:2605.20519v1 Announce Type: cross Abstract: Prior attacks on Audio Large Language Models (Audio LLMs) demonstrated that carefully crafted waveform-domain perturbations can force targeted adversa

applicationsarxiv-cs-ai

Cohesion-6K: An Arabic Dataset for Analyzing Social Cohesion and Conflict in Online Discourse

arXiv:2605.22447v1 Announce Type: new Abstract: The study of online discourse has become central to understanding societal polarization. While much research has focused on detecting overt toxicity, th

D3Seg: Dependency-Aware Diffusion for Brain Tumor Segmentation with Missing Modalities

arXiv:2605.22249v1 Announce Type: new Abstract: Accurate brain tumor segmentation using multiparametric MRI is critical for effective treatment planning. However, in clinical settings, complete acquis

researcharxiv-cs-cv

Entropy-Guided Self-Supervised Learning for Medical Image Classification

arXiv:2605.21970v1 Announce Type: cross Abstract: Accurate and robust medical image classification is paramount for early disease diagnosis and treatment planning. However, challenges such as limited

researcharxiv-cs-cv

FashionLens: Toward Versatile Fashion Image Retrieval via Task-Adaptive Learning

arXiv:2605.22552v1 Announce Type: new Abstract: Fashion image retrieval is a cornerstone of modern e-commerce systems. A unified framework that supports diverse query formats and search intentions is

Geometry-Adaptive Explainer for Faithful Dictionary-Based Interpretability under Distribution Shift

arXiv:2605.21849v1 Announce Type: cross Abstract: Mechanistic interpretability aims to explain a model's behavior by identifying causally responsible internal structures. Dictionary-based explainers s

researcharxiv-cs-cl

ha ha, so much for step change? maybe this problem was just easier than some?

model-releasesgary-marcus--x

ha ha, so much for step change? maybe this problem was just easier than some? The standard GPT-5.5 reproduced the proof ~ 👇 https://chatgpt.com/share/6a0e9e04-8cb0-8332-a4f1-ec68acd2e03e You don't nee

Highlighting the new WebGPU backend in llama.cpp/ggml The work to bring full-fledged WebGPU support in llama.cpp started about an year and a…

model-releasesgeorgi-gerganov--x

Highlighting the new WebGPU backend in llama.cpp/ggml The work to bring full-fledged WebGPU support in llama.cpp started about an year and a half ago. It has been lead by @reeselevine and team at USCS

HyLoVQA: Dynamic Hypernetwork-Generated Low-Rank Adaptation for Continual Visual Question Answering

arXiv:2605.22035v1 Announce Type: cross Abstract: Continual Visual Question Answering (VQA) requires learning from non-stationary streams of visual inputs and questions while preserving past knowledge

InfVSR: Breaking Length Limits of Generic Video Super-Resolution

arXiv:2510.00948v2 Announce Type: replace Abstract: Real-world videos often extend over thousands of frames. Existing generative video super-resolution (VSR) approaches, however, face two persistent c

Link to GPT 5.5 on the recent Erdo problem: https://x.com/maxiao54704/status/2057484153755480537?s=61

model-releasesgary-marcus--x

Link to GPT 5.5 on the recent Erdo problem: https://x.com/maxiao54704/status/2057484153755480537?s=61 The standard GPT-5.5 reproduced the proof ~ 👇 https://chatgpt.com/share/6a0e9e04-8cb0-8332-a4f1-ec

MLLMs Know When Before Speaking: Revealing and Recovering Temporal Grounding via Attention Cues

arXiv:2605.21954v1 Announce Type: new Abstract: Video temporal grounding (VTG), which localizes the start and end times of a queried event in an untrimmed video, is a key test of whether multimodal la

MM-Conv: A Multimodal Dataset and Benchmark for Context-Aware Grounding in 3D Dialogue

arXiv:2605.21796v1 Announce Type: cross Abstract: Grounding language in the physical world requires AI systems to interpret references that emerge dynamically during conversation. While current vision

MOTOR: A Multimodal Dataset for Two-Wheeler Rider Behavior Understanding

arXiv:2605.22550v1 Announce Type: new Abstract: Two-wheelers account for a disproportionately high share of road fatalities in the Global South. Research on two-wheeler rider behavior, however, lags f

NaviAgent: Graph-Driven Bilevel Planning for Scalable Tool Orchestration

arXiv:2506.19500v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) increasingly act as function-call agents that invoke external tools to tackle tasks beyond their static knowledge

safetyarxiv-cs-cl

Open-source LLMs administer maximum electric shocks in a Milgram-like obedience experiment

arXiv:2605.21401v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents that make sequences of decisions over extended interactions in high-stakes

safetyarxiv-cs-ai

PromptNCE: Pointwise Mutual Information Predictions Using Only LLMs and Contrastive Estimation Prompts

arXiv:2605.21776v1 Announce Type: new Abstract: Estimating mutual information from text usually requires training a task-specific critic, which limits its use in low-data settings. We ask whether larg

Applications

Quantizing Whisper-small: How design choices affect ASR performance

arXiv:2511.08093v2 Announce Type: replace-cross Abstract: Large speech recognition models like Whisper-small achieve high accuracy but are difficult to deploy on edge devices due to their high computa

applicationsarxiv-cs-cl

Local Ai

SegCompass: Exploring Interpretable Alignment with Sparse Autoencoders for Enhanced Reasoning Segmentation

arXiv:2605.22658v1 Announce Type: new Abstract: While large language models provide strong compositional reasoning, existing reasoning segmentation pipelines fail to transparently connect this reasoni

local-aiarxiv-cs-cv

SFN-YOLO: Towards Free-Range Poultry Detection via Scale-aware Fusion Networks

arXiv:2509.17086v2 Announce Type: replace Abstract: Detecting and localizing poultry is essential for advancing smart poultry farming. Despite the progress of detection-centric methods, challenges per

Agents

SpecHop: Continuous Speculation for Accelerating Multi-Hop Retrieval Agents

arXiv:2605.21965v1 Announce Type: new Abstract: Large language models increasingly use external tools such as web search and document retrieval to solve information-intensive tasks. However, multi-hop

agentsarxiv-cs-cl

ST-SimDiff: Balancing Spatiotemporal Similarity and Difference for Efficient Video Understanding with MLLMs

arXiv:2605.22158v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) face significant computational overhead when processing long videos due to the massive number of visual token

researcharxiv-cs-cv

Steins;Gate Drive: Semantic Safety Arbitration over Structured Futures for Latency-Decoupled LLM Planning

model-releasesarxiv-cs-ro

arXiv:2605.22456v1 Announce Type: new Abstract: Cloud-hosted LLM driver agents provide useful semantic judgments, but their inference latency exceeds stepwise vehicle-control windows. Learned world mo