Search: “inference”

arXiv:2608.25190v1 Announce Type: new Abstract: Fake news detection has become an important Natural Language Processing (NLP) task due to the rapid spread of misinformation through online news platfor

hardwarearxiv-cs-cl

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Beyond Optimal Rates in Stochastic Optimization: Trajectory-Adaptive Stopping Rules

DGX agent

arXiv:2608.25551v1 Announce Type: new Abstract: Stochastic gradient descent (SGD) is typically analyzed at a deterministic horizon chosen before the algorithm is run, even though practical stopping de

researcharxiv-cs-lg

27 Aug 2026

CEDAR: Controlled and Event-Driven Demand Forecasting via Residual Decomposition

arXiv:2608.25871v1 Announce Type: new Abstract: Forecasting in large-scale e-commerce marketplaces is increasingly required to support planning: merchants need to evaluate sales outcomes under future

safetyarxiv-cs-lg

Clearing the Underbrush: AI-Enhanced RF Interference Suppression

arXiv:2608.24974v1 Announce Type: new Abstract: AI-based structured interference rejection has grown more popular because deep learning approaches can outperform traditional methods by jointly conside

Cluster-Dags as Powerful Background Knowledge For Causal Discovery

arXiv:2512.10032v3 Announce Type: replace Abstract: Finding cause-effect relationships is of key importance in science. Causal discovery aims to recover a graph from data that succinctly describes the

Deploy personal AI agents with Cloud Run instances

Need a low-cost, high-performance way to run long-lived, stateful workloads such as AI agents? Today, we introduced Cloud Run instances, which let you do just that. Consider AI agents such as OpenClaw

safetygoogle-cloud-ai

EncoTESS: Age-Sensitive Encodings from Raw TESS Light Curves

arXiv:2608.25019v1 Announce Type: cross Abstract: Main sequence stars of spectral types late F through M exhibit systematic variability in photometric light curves, particularly when they are young. R

Fast rates in Bayesian online learning with approximate posteriors

arXiv:2608.25706v1 Announce Type: cross Abstract: Exact Bayes prediction enjoys fast predictive regret guarantees, but exact posterior updating or representation may be too costly for online use. We s

Generative Modeling: A Review

arXiv:2501.05458v3 Announce Type: replace-cross Abstract: We organize the generative-modeling literature around three classes of generators, corresponding to three distinct inferential tasks: estimati

Local Ai

GLM-5.3-Flash @ DGX Station GB300: ~206 tok/s (single stream), 1M context

Hey all! I'm finally doing some cool stuff with my 'thinking heater' (h/t u/-TV-Stand-). I'm still experimenting with GLM-5.2 (in anticipation of 5.3 coming tomorrow, I hope!) and things are very cool

local-air-localllama

Group-Shared Low-Rank Approximation for Mobile-Efficient Pointwise Convolutions in Large-Kernel CNNs

arXiv:2608.26069v1 Announce Type: new Abstract: Large-kernel Convolutional Neural Networks (CNNs) deliver remarkable performance in vision tasks by significantly expanding receptive fields, yet their

Improved Analysis for Hessian-free High-resolution Monte Carlo Sampling

arXiv:2608.25052v1 Announce Type: cross Abstract: Hessian-free high-resolution (HFHR) dynamics augments underdamped Langevin dynamics (ULD) with reversible position diffusion for sampling problems tha

InteractGesture: Progressive Chunk Guidance for Continuous Streaming Co-Speech Gesture Control

arXiv:2608.25734v1 Announce Type: new Abstract: Co-speech gesture generation has made significant progress toward realistic full-body motion from speaker audio, yet existing models lack fine-grained s

researcharxiv-cs-cv

Applications

Label-Free Foundational Model Selection for Medical Image Classification under Distribution Shift via Pseudo Label Discrepancy

arXiv:2608.25810v1 Announce Type: new Abstract: Foundation models are increasingly deployed for medical image analysis. However, under the inter-institutional distribution shift typical of deployment,

applicationsarxiv-cs-cv

Learning Late, Guiding Early: Timestep-Decoupled Semantic Guidance for Fair Face Generation

arXiv:2608.25862v1 Announce Type: new Abstract: Demographic imbalance in synthetic face generation can propagate to downstream face recognition systems, making fairness an important consideration when

safetyarxiv-cs-cv

Local Ai

LM-X: Explainable Action Modeling with Progress, Event, and Uncertainty Prediction for Generalist Robot Manipulation

arXiv:2608.25757v1 Announce Type: cross Abstract: Generalist vision--language--action (VLA) policies learn long-horizon behavior mainly through short-horizon action prediction and reveal little beyond

local-aiarxiv-cs-lg

Multi-output Gaussian process prediction of physical fields under linear equality constraints

arXiv:2608.25709v1 Announce Type: cross Abstract: We address the simultaneous prediction of multiple high-dimensional physical fields governed by linear equality constraints, a setting that arises in

NVExplain: Explaining Time Series Forecasting with Latent Trajectory Analysis and Structure-Preserving Surrogates

arXiv:2608.25080v1 Announce Type: new Abstract: Time series forecasting models are widely used in high-stakes settings, yet their predictions remain difficult to interpret because existing post-hoc me

One Policy, Many Embodiments: Unified Camera-Centric Action Geometry Pre-training for Heterogeneous Embodied Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.26058v1 Announce Type: new Abstract: Scaling generalist vision-language-action (VLA) policies is severely bottlenecked by the inherent heterogeneity of embodied data, which spans diverse ro

PANDA - Prototype-Anchored Alignment for Partially Unpaired Multimodal Learning, with Applications to Alzheimers MRI and TCGA Pathology

arXiv:2608.25970v1 Announce Type: new Abstract: Multimodal medical prediction often faces incomplete pairing: auxiliary modalities with complementary signal are available for only a subset of subjects

safetyarxiv-cs-cv

Pointing the Way, Hiding the Destination: Practical Private Dense Retrieval at Scale

arXiv:2608.25735v1 Announce Type: cross Abstract: Hosted retrieval-augmented generation (RAG) and semantic search allow users to query valuable provider-held corpora, raising two competing demands: to

Reconstructing the Right Episode: Evaluating Interleaved Conversational Memory Beyond Long Context

model-releasesarxiv-cs-cl

arXiv:2608.25655v1 Announce Type: new Abstract: Conversations with chat assistants increasingly span many topics in a single long-running thread, challenging memory systems. Existing long-context and

Scalable Self-Supervised Learning for Multiphase AC-OPF in Distribution Systems with Topology Reconfiguration

arXiv:2608.25095v1 Announce Type: cross Abstract: The proliferation of distributed energy resources (DERs) in distribution grids enables the active coordination of these assets to reduce costs and ena

SNAP-KG: Streaming Node Assignment via Projection for Knowledge Graph Entity Integration

arXiv:2608.25149v1 Announce Type: new Abstract: Knowledge graph (KG) construction pipelines must continuously integrate newly arriving entities into a growing graph. Unlike inserting triples between e

Theoretically Principled Federated Learning for Balancing Privacy and Utility

arXiv:2305.15148v3 Announce Type: replace Abstract: We propose a general learning framework for the protection mechanisms that protects privacy via distorting model parameters, which facilitates the t

Hardware

TOPAS: Workflow-Aware Prefix-State Scheduling for Multi-Agent LLM Serving

arXiv:2608.25523v1 Announce Type: new Abstract: Prefix caching introduces a fundamental tradeoff in multi-agent large language model (LLM) serving: retaining a long system-prompt key-value (KV) cache

hardwarearxiv-cs-cl

Towards Fine-Grained Text-to-3D Quality Assessment: A Benchmark and A Two-Stage Rank-Learning Metric

model-releasesarxiv-cs-cv

arXiv:2509.23841v3 Announce Type: replace Abstract: Recent advances in Text-to-3D (T23D) generative models have enabled the synthesis of diverse, high-fidelity 3D assets from textual prompts. However,

Agents

We've introduced native, agentic spreadsheet extraction 📊 into LlamaParse. Spreadsheets are a wildly different format from PDFs (or any oth…

We've introduced native, agentic spreadsheet extraction 📊 into LlamaParse. Spreadsheets are a wildly different format from PDFs (or any other document format). They can span arbitrarily many rows/colu

agentsjerry-liu--x

A Structural FHMM for Interpretable Disease Trajectories in T2DM

arXiv:2608.24328v1 Announce Type: new Abstract: In this work, we propose a structural variant of the Factorial Hidden Markov Model (FHMM) for the analysis of disease trajectories in patients with Type

Adaptive prediction theory combining offline and online learning

arXiv:2512.00342v2 Announce Type: replace Abstract: Real-world intelligence systems usually operate by combining offline learning and online adaptation with highly correlated and non-stationary system

Agents

AgentWorld: Personality-Aware Reliability Evaluation for Agentic Information Retrieval

arXiv:2608.24076v1 Announce Type: new Abstract: Evaluation of agentic information retrieval remains limited to scripted interactions with uniform users, missing both natural personality diversity and

agentsarxiv-cs-ai

Hardware

Amazing! 🥳 Thanks @vllm_project for getting Qwen3.8-Flash-Next running on NVIDIA and AMD from day 0.

Amazing! 🥳 Thanks @vllm_project for getting Qwen3.8-Flash-Next running on NVIDIA and AMD from day 0. Qwen3.8-Flash-Next from @Alibaba_Qwen has day-0 support in vLLM, verified on NVIDIA and AMD GPUs. 🎉

hardwareqwen--x

Bridging Adversarial and Collaborative Learning for AI-Generated Image Quality Assessment

arXiv:2608.24372v1 Announce Type: new Abstract: AI-generated image quality assessment (AIGIQA) requires jointly reasoning about perceptual fidelity and prompt alignment, two quality dimensions that ar

safetyarxiv-cs-cv

ChorusTIC: Training-Free Multivariate Time Series Classification via Chorus In-Context Learning

arXiv:2608.24033v1 Announce Type: cross Abstract: Time series classification underpins applications in healthcare, sensing, and industrial monitoring. Although time series foundation models support fo

CoDrift: Compositional Drifting for Offline Reinforcement Learning

arXiv:2608.23939v1 Announce Type: new Abstract: Offline reinforcement learning is intrinsically multi-objective: a policy must remain compatible with the behavioral support of a fixed dataset while pr

safetyarxiv-cs-lg

Coronavirus Optimization Algorithm: A Success-History Adaptive Evolutionary Framework with Archive-Assisted Search and Stagnation Recovery for Global Optimization

arXiv:2608.23847v1 Announce Type: cross Abstract: This paper proposes the Coronavirus Optimization Algorithm (COA), a SARS-CoV-2-inspired success-history adaptive evolutionary optimizer for box-constr

Disentangled Skill Representations for Predictive Human Modeling

arXiv:2608.23776v1 Announce Type: cross Abstract: Understanding human skill is important for AI systems that collaborate with, coach, or assist people. Unlike typical latent variable estimation proble

researcharxiv-cs-ai

Gated Activation Steering for Reducing Sycophancy & Hallucination in Medical Question Answering

arXiv:2608.23666v1 Announce Type: new Abstract: Sycophancy and hallucination are persistent failure modes of Large Language Models (LLMs) across domains. However, it becomes particularly consequential

Applications

Generating Intervention Hypotheses using Explainable Explanations on Graphs: G2I, a Two-Stage Greedy Framework

arXiv:2608.23835v1 Announce Type: new Abstract: Real-world decision-making in public health and social science can greatly benefit from predictive models, yet translating predictions into effective in

applicationsarxiv-cs-lg

ICA: Information-Aware Credit Assignment for Visually Grounded Long-Horizon Information-Seeking Agents

arXiv:2602.10863v2 Announce Type: replace-cross Abstract: Long-horizon reinforcement learning for information seeking agents remains difficult because terminal rewards reveal whether the final answer

Joint Optimization of Tool Creation and Use for Large Language Model Agents

arXiv:2608.24571v1 Announce Type: new Abstract: Tool-augmented language models are bounded by the APIs humans bothered to write; existing tool-creation systems patch this by prompting a frozen LLM at

safetyarxiv-cs-ai

Latent Action as Intention Enables Efficient Future Imagination for World Action Models

model-releasesarxiv-cs-ro

arXiv:2608.24882v1 Announce Type: new Abstract: World action models (WAMs) improve robot control by modeling how observations evolve, but generating future observations at test time incurs substantial

NeuronGuard: Robust LLM Safety Alignment via Ablation-Aware Safety Signal Redistribution

arXiv:2608.23959v1 Announce Type: cross Abstract: Safety alignment in large language models (LLMs) remains brittle against a growing spectrum of attacks. Jailbreak attacks bypass safety mechanisms thr

safetyarxiv-cs-ai

NeuronTune: Fine-Grained Neuron Modulation for Balanced Safety-Utility Alignment in LLMs

arXiv:2508.09473v2 Announce Type: replace-cross Abstract: Ensuring robust safety alignment while preserving utility is critical for the reliable deployment of Large Language Models (LLMs). However, cu

safetyarxiv-cs-ai

Local Ai

NeurRAFT: Robot Motion Planning via Anchor-Level Flow Matching with Clearance-Aware Preference Tuning

arXiv:2608.24026v1 Announce Type: new Abstract: Recent end-to-end neural motion planners generate trajectories from raw sensor observations, avoiding the privileged geometric models required by classi

local-aiarxiv-cs-ro

Agents

Nutanix expands cloud platform with controls for agentic AI

Nutanix Inc. today introduced new capabilities intended to help enterprises run agentic artificial intelligence applications alongside existing virtual machines and containerized workloads without spl

agentssiliconangle

NVIDIA Cosmos-H-Dreams: Real-Time Generative Physics Simulation for Surgical Robotics

arXiv:2608.24199v1 Announce Type: new Abstract: Generative simulation for surgical robotics still lacks real-time interaction. Physical-robot experiments, often involving animal or cadaver labs, are t

safetyarxiv-cs-ro

ORBITALIF: An Efficient Spiking Federated Learning Framework for Onboard Cloud Removal

arXiv:2608.24073v1 Announce Type: cross Abstract: Low-earth-orbit (LEO) satellites enable high-resolution, large-scale Earth observation for applications such as disaster monitoring and environmental