Search: “inference”

Evaluating AI Generated Summaries for Cancer Patients

arXiv:2608.26154v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into digital health platforms to generate summaries of complex medical data. Although t

safetyarxiv-cs-ai

Fairness Invariants: A Relational Approach to Explaining and Mitigating Fairness Bugs

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DGX agent

arXiv:2608.26209v1 Announce Type: cross Abstract: Data-driven software systems are increasingly deployed in high-stakes socio-economic domains, from criminal justice to financial lending. However, the

local-aiarxiv-cs-ai

28 Aug 2026

Agents

Finding the Right Evidence: Factor-Guided Coarse-to-Fine Reasoning for Long Videos

arXiv:2608.26355v1 Announce Type: new Abstract: While LVLMs rapidly improve, long-video question answering still remains challenging: relevant evidence is sparse, and question-relevant context often f

agentsarxiv-cs-cv

GSM8K-V: Can Vision Language Models Solve Grade School Math Word Problems in Visual Contexts

model-releasesarxiv-cs-ai

arXiv:2509.25160v2 Announce Type: replace-cross Abstract: Mathematical reasoning is a key capability for vision-language models (VLMs), yet current benchmarks mainly evaluate text-based or explicitly

hoBIT: A Profile-Aware Retrieval-Augmented Chatbot for University Academic Advising

arXiv:2608.26604v1 Announce Type: cross Abstract: In university academic advising, identical questions can require different answers depending on a student's department, admission cohort, and degree p

Multivariate Diffusion Transformer with Decoupled Attention for High-Fidelity Mask-Text Collaborative Facial Generation

arXiv:2511.12631v3 Announce Type: replace-cross Abstract: While significant progress has been achieved in multimodal facial generation using semantic masks and textual descriptions, conventional featu

researcharxiv-cs-ai

Applications

Neural Regression with Embeddings for Numerical Attribute Prediction in Knowledge Graphs

arXiv:2608.26729v1 Announce Type: new Abstract: In recent years, transductive knowledge graph embedding models have been applied to tasks such as link prediction and query answering. Although knowledg

applicationsarxiv-cs-lg

On the Indistinguishability of Human v/s AI Generated Text

arXiv:2608.26797v1 Announce Type: new Abstract: The rapid improvement of LLMs has made distinguishing AI-generated text from human writing a pressing problem. This challenge is further amplified by pa

RubricRM: Generative Reward Modeling via Dynamic Rubrics for Image Generation and Editing

arXiv:2608.26956v1 Announce Type: new Abstract: Reward models play an essential role in aligning visual generative models, yet most existing visual reward models use a single scalar score or rely on f

researcharxiv-cs-cv

Self-Augmented Diffusion Guidance for Physics-Informed Generation

arXiv:2608.26748v1 Announce Type: new Abstract: Diffusion models can be used to generate spatiotemporal signals of physical phenomena, such as time-series images of fluid dynamics. However, a major li

Sharp Minimax Regret for Infinite-Memory Logistic Prediction

arXiv:2608.26515v1 Announce Type: cross Abstract: We study online prediction for a specific finite-alphabet, exogenously driven source with infinite input memory. Independent Rademacher inputs (U_t) a

local-aiarxiv-cs-lg

Simple Actors and Deep Critics for Scalable Reinforcement Learning

arXiv:2608.26659v1 Announce Type: new Abstract: Recent progress in offline reinforcement learning (RL) has been driven by expressive generative actors such as diffusion and flow-matching policies, whi

SLM-Conditioned Hierarchical Relation Routing for Labeled Property Graph Learning

model-releasesarxiv-cs-cl

arXiv:2608.26132v1 Announce Type: cross Abstract: Labeled property graphs combine relational structure with heterogeneous textual and categorical properties attached to both nodes and relationships. C

Temporally-Grounded Language Generation: Towards Real-Time Vision-Language Models

model-releasesarxiv-cs-ai

arXiv:2505.11326v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have shown remarkable progress in offline tasks such as image captioning and video question answering. However,

The Accuracy-Efficiency Paradox Quantifying Net Energy Loss in on-Device Energy Forecasting

arXiv:2608.26134v1 Announce Type: new Abstract: Energy forecasting aims to maximize accuracy to ensure energy efficiency by reducing energy waste, an objective that applies equally to on-device foreca

local-aiarxiv-cs-ai

Vision-centric generative AI models: A software-hardware perspective

model-releasesarxiv-cs-cv

arXiv:2608.27199v1 Announce Type: new Abstract: Vision generative artificial intelligence (AI) has emerged as one of the most rapidly advancing areas of deep learning. The explosion of multimodal mode

When Interference Graphs Evolve: Doubly Robust Estimation of Dynamic Peer Effects

arXiv:2608.27187v1 Announce Type: new Abstract: Peer effects are difficult to estimate when interaction graphs evolve because pre-assignment network history, dynamic peer exposure, and post-assignment

Adversarial Training of Linear Models under Stealthy Attacks

arXiv:2608.25681v1 Announce Type: new Abstract: Predictive models are widely used in many fields, but are vulnerable to false data injection attacks. To address this, detection schemes and adversarial

ARGenSeg: Image Segmentation with Autoregressive Image Generation Model

arXiv:2510.20803v2 Announce Type: replace Abstract: We propose a novel AutoRegressive Generation-based paradigm for image Segmentation (ARGenSeg), achieving multimodal understanding and pixel-level pe

researcharxiv-cs-cv

Hardware

BanglaMamba: Exploring State Space Models for Bangla Fake News Detection

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

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

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

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

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

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

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,

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

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