Search: “models”

arXiv:2609.01212v1 Announce Type: new Abstract: With the rapid and continuous growth in the incorporation of machine learning models based on the Transformer architecture, capable deployment is in hig

tutorialsarxiv-cs-lg

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

ReDeck: Step-Level Render-Grounded Refinement for Document-to-Slide Generation

DGX agent

arXiv:2609.00194v1 Announce Type: new Abstract: Document-to-slide generation is challenging because slides are dense editable artifacts that require both faithful content selection and precise spatial

model-releasesarxiv-cs-ai

2 Sept 2026

Relational Task Generation Language: A Declarative Specification Framework for Relational Deep Learning

model-releasesarxiv-cs-lg

arXiv:2609.01292v1 Announce Type: cross Abstract: Relational Deep Learning (RDL) has become a powerful paradigm for learning from multi-tabular data. However, manually defining RDL prediction tasks is

Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents

arXiv:2609.00065v1 Announce Type: cross Abstract: A language-model agent asked to analyse an experiment will usually return working code. Whether the analysis is defensible is a different question. A

Semantic-Guided Multimodal Preprocessing for Vision Transformer-Based Clear Cell Renal Cell Carcinoma Grading

arXiv:2609.01426v1 Announce Type: cross Abstract: Clear cell renal cell carcinoma (CCRCC) grading is essential for treatment planning, yet existing approaches either analyze patch-level images directl

researcharxiv-cs-ai

Sierpinski--Knopp Wasserstein Distance for Persistence Diagrams and Applications to 2-Wasserstein Approximation

model-releasesarxiv-cs-lg

arXiv:2609.01528v1 Announce Type: cross Abstract: This paper introduces the Sierpinski-Knopp (SK) Wasserstein distance, a fast metric between persistence diagrams. The SK-Wasserstein distance, denoted

Staged Linguistic Seeding: Grounded Query Expansion for Verified-Unit QA in AI Contact Centers

model-releasesarxiv-cs-cl

arXiv:2609.00844v1 Announce Type: new Abstract: Customer-service QA in an AI contact center (AICC) runs under deployment constraints that benchmark QA misses: tight voice-hotline latency and a high co

Task-Specific Prompt with Global Context for Multi-Task Graph Pre-Training

arXiv:2609.00047v1 Announce Type: cross Abstract: Graph prompt learning is an effective paradigm to adapt pre-trained graph models to downstream tasks in low-resource scenarios. However, existing mult

The Rise of Verbal Reinforcement Learning

arXiv:2609.01597v1 Announce Type: cross Abstract: Natural language is emerging as a primary feedback channel for improving language agents, capable of conveying intent, preferences, and causal structu

Toward Workflow-Aware Benchmarking for Healthcare NLP Agents

arXiv:2609.00296v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly proposed for healthcare tasks such as clinical documentation, evidence retrieval, patient messaging,

agentsarxiv-cs-cl

Towards Provable and Scalable Training of Quantized Neural Networks with Ising Optimization

arXiv:2506.18240v5 Announce Type: replace-cross Abstract: Training quantized neural networks remains fundamentally challenging due to non-convex loss landscapes and discrete parameter spaces. We intro

TRIS: A Tri-Layer Retrieval Integrity Sieve Against Knowledge Poisoning

arXiv:2609.00470v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) grounds large language models in external corpora, but implicit trust in retrieved documents creates a critical att

researcharxiv-cs-cl

TRUST: Threshold-Recalibrated Uncertainty-Safe Training for Certified Dismissal in Breast Cancer Screening

arXiv:2609.00300v1 Announce Type: new Abstract: Reducing the review of clearly cancer-negative screening mammograms could lower radiologist workload without compromising cancer detection. We propose a

researcharxiv-cs-cv

Applications

TUTTI: Toward generalizable audio-to-score transcription via fully synthesized data

arXiv:2609.00640v1 Announce Type: cross Abstract: Generalizable Audio-to-Score (A2S) transcription is fundamentally constrained by the severe scarcity of high-quality, real-world paired data. Relying

applicationsarxiv-cs-ai

TWIX: a Two-Stage Approach for End-To-End Named Entity Recognition and Relation Extraction

model-releasesarxiv-cs-cl

arXiv:2609.00832v1 Announce Type: new Abstract: The exponential growth of scientific publications calls for automatic Information Extraction (IE) systems to support knowledge discovery. In this contex

Uncovering and Mitigating Aggregation-Induced Reward Hacking in Multi-Reward Reinforcement Learning

arXiv:2609.00213v1 Announce Type: new Abstract: Reinforcement learning fine-tuning of large language models increasingly adopts multiple reward dimensions, including verifiable rules, task-specific ev

safetyarxiv-cs-cl

V-Co: A Closer Look at Visual Representation Alignment via Co-Denoising

arXiv:2603.16792v2 Announce Type: replace-cross Abstract: Pixel-space diffusion has recently re-emerged as a strong alternative to latent diffusion, enabling high-quality generation without pretrained

VerNav: Verifier-First Low-Latency Vision-and-Language Navigation

arXiv:2609.00920v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) requires an agent to navigate through unseen 3D environments according to natural-language instructions. Explicit

Vision-Language-Guided Pseudo-Labels for Unsupervised Domain Adaptation in Semantic Segmentation for Waste Sorting

arXiv:2609.00898v1 Announce Type: cross Abstract: Obtaining labeled data for semantic segmentation in applied settings (e.g., autonomous driving, industrial waste sorting) is expensive and often infea

Tutorials

(V)LMs generalize beyond surface co-occurrence: Evidence from cross-modal number agreement

arXiv:2609.00443v1 Announce Type: cross Abstract: Language models learn about grammatical number primarily from co-occurrence, and show frequency effects as a result---sometimes taken to indicate that

tutorialsarxiv-cs-ai

When Features Become Instances: Inverted Contrastive Learning for Unsupervised Feature Selection

arXiv:2609.00782v1 Announce Type: new Abstract: Unsupervised feature selection seeks a compact subset of informative features without access to class labels, making feature utility difficult to define

WiseSpec: Requirements-Driven Agents for Code Generation

arXiv:2609.00568v1 Announce Type: cross Abstract: Code generation aims to automatically generate source code from task requirements and has attracted significant attention with the rapid advancement o

Zero-Shot Respiratory Sound Classification through LLM-Augmented Audio-Text Alignment

arXiv:2609.00055v1 Announce Type: cross Abstract: Self-supervised respiratory encoders lack semantic grounding in clinical domain needed for zero-shot inference, limiting their utility without task-sp

Hardware

A-MADiff: Attention-Guided Multi-Agent DRL with Diffusion Policies for Memory-Aware Task Orchestration in Mobile AIGC Networks

arXiv:2608.29255v1 Announce Type: cross Abstract: Artificial Intelligence-Generated Content (AIGC) services employ Generative AI (GenAI) models to automatically generate diverse content. Mobile AIGC n

hardwarearxiv-cs-lg

A Multi-Agent Human-LLM Collaborative Framework for Closed-Loop Scientific Literature Summarization

arXiv:2604.01452v2 Announce Type: replace Abstract: Scientific discovery is slowed by fragmented literature that requires excessive human effort to gather, analyze, and understand. AI tools, including

AdaPath: Query-Adaptive Path-Finding via Path-Bank for Multi-Hop Implicit Biomedical KGQA

arXiv:2608.30556v1 Announce Type: new Abstract: Path-finding over knowledge graphs has become an effective way to ground LLM reasoning on multi-hop questions. However, biomedical QA introduces two dis

Adaptive teachers for amortized samplers

arXiv:2410.01432v3 Announce Type: replace Abstract: Amortized inference is the task of training a parametric model, such as a neural network, to approximate a distribution with a given unnormalized de

safetyarxiv-cs-lg

Adversarial Calibration Attack on Autonomous Vehicles

arXiv:2608.28778v1 Announce Type: cross Abstract: Autonomous vehicles (AVs) rely on accurate camera-LiDAR calibration for multimodal sensor fusion. In practice, calibration can drift due to vibration,

Agent Zero Memory: Provenance-Aware Long-Term Memory for LLM Agents

arXiv:2608.29606v1 Announce Type: new Abstract: Large language model (LLM) agents need durable, faithful memory of everything a user or organization has said and stored, yet most memory systems commit

agentsarxiv-cs-cl

Agent2UCB: Agentic System for Generative Engine Optimization

arXiv:2608.29063v1 Announce Type: new Abstract: Large language model driven search engines such as Google AI Overviews and Perplexity have created new opportunities for Generative Engine Optimization

AgenTRIM: Tool Risk Mitigation for Agentic AI

arXiv:2601.12449v2 Announce Type: replace-cross Abstract: AI agents are autonomous systems that combine LLMs with external tools to solve complex tasks. While such tools extend capability, improper to

AgentRx: Diagnosing AI Agent Failures from Execution Trajectories

arXiv:2602.02475v2 Announce Type: replace Abstract: AI agents often fail in ways that are difficult to localize because executions are probabilistic, long-horizon, multi-agent, and mediated by noisy t

Alert: Learning Trigger Functions for Early Classification of Time Series using Deep-RL

model-releasesarxiv-cs-lg

arXiv:2502.06584v2 Announce Type: replace Abstract: Early Classification of Time Series (ECTS) is vital in fields like industrial monitoring and medical triage, where quick and accurate predictions ar

Amortized Anchor Refinement for Deployable Continuous-Time 4D Gaussian Reconstruction

arXiv:2608.30218v1 Announce Type: new Abstract: Continuous-time 4D reconstruction remains impractical on standalone XR headsets. Per-scene optimization demands deployment-infeasible compute, and lower

Applications

AOI-Net: Structural Face AOI-Guided Eye-Gaze Track Representation Learning for Autism Spectrum Disorder Detection

arXiv:2608.29289v1 Announce Type: cross Abstract: Eye-movement tracking has emerged as a promising non-invasive approach to Autism Spectrum Disorder (ASD) screening, with systematic differences in att

applicationsarxiv-cs-ai

Applications of Risk Science to AI Fairness Evaluation: Principles, Challenges, and Best Practices

arXiv:2608.29478v1 Announce Type: cross Abstract: Scholarly work which aims to describe potential societal impacts (e.g., risks) of proliferating technology (especially related to artificial intellige

ASTRA - Agentic System for Ticket Resolution and Analysis

arXiv:2608.28790v1 Announce Type: cross Abstract: Technical operations teams resolve large volumes of incidents by synthesizing fragmented evidence from ticket text, historical cases, system logs, and

Applications

Audio-Driven Adversarial Defense for 3D Talking Face Generation with totally Visual Fidelity Preservation

arXiv:2608.30951v1 Announce Type: new Abstract: The rapid development of generative portrait models has raised growing concerns about privacy leakage and identity misuse. In particular, audio-driven 3

applicationsarxiv-cs-cv

Augmenting Human Performance with an XR Agent Learning from Online Behavior and BCI Evidence

arXiv:2608.30369v1 Announce Type: new Abstract: We present OLIVE, a framework for adapting a foundation model to provide real-time assistance in temporally demanding, high-stakes, and dynamic tasks. W

Bayesian-Optimized Superpixel-GrabCut for Traceable Optic Disc Segmentation

arXiv:2608.29196v1 Announce Type: new Abstract: Optic disc (OD) segmentation is essential for diagnosing ophthalmic pathologies from retinal fundus images. However, prevailing deep learning approaches

Behavior-Skill: A Fine-Grained Benchmark for Evaluating Vision-Language-Action Policies in Long-Horizon Tasks

model-releasesarxiv-cs-ro

arXiv:2608.30536v1 Announce Type: new Abstract: Reliable execution of long-horizon mobile manipulation tasks remains challenging because overall task success depends on the successful completion of mu

Behavioral Latency as Weak Event-Time Supervision for EEG Reaction-Time Decoding

arXiv:2608.29428v1 Announce Type: new Abstract: Single-trial EEG analyses are often organized around events and latencies, yet EEG-based reaction-time (RT) prediction is posed as scalar regression on

safetyarxiv-cs-lg

Benevolent Bias in Multi-Turn Human-Agent Dialogue

arXiv:2608.29206v1 Announce Type: new Abstract: Bias in human-agent interaction can manifest not only through hostile language but also as benevolent bias, whereby unequal treatment hides behind a war

Beyond NL2Code: A Structured Survey of Multimodal Code Intelligence

arXiv:2606.15932v3 Announce Type: replace Abstract: While Large Language Models (LLMs) have substantially advanced text-to-code generation, many real programming tasks specify intent through visual ar

agentsarxiv-cs-cl

Beyond the Payload: How User Invocation Shapes Coding Agent Vulnerability to Repository Poisoning

model-releasesarxiv-cs-cl

arXiv:2608.30686v1 Announce Type: cross Abstract: Coding agents are increasingly used for software engineering tasks, including bootstrapping projects from third-party repositories whose integrity can

Beyond Uncertainty: Multi-Solver Disagreement Rewards for Self-Evolving Reasoning Curricula

arXiv:2608.30035v1 Announce Type: new Abstract: Self-evolving reasoning frameworks train a Challenger to generate questions exposing a Solver's weaknesses, creating adaptive curricula without human da

researcharxiv-cs-ai

ButterMamba: Butterworth-Enhanced Spatial-Temporal Mamba for Efficient Traffic Flow Prediction

arXiv:2608.29658v1 Announce Type: cross Abstract: Accurate traffic flow prediction is fundamental to intelligent transportation systems, playing a pivotal role in urban mobility optimization and smart

researcharxiv-cs-lg

CANVAS: Consistency-Aware Navigation via Visual Adaptive Sampling for Long-Context Text-to-SVG Generation

arXiv:2608.30689v1 Announce Type: new Abstract: Autoregressive large models have recently advanced Text-to-SVG generation from simple icons to complex, long-context graphics, yet standard autoregressi

researcharxiv-cs-cv