Search: “framework”

CANDOR: Counterfactual ANnotated DOubly Robust Off-Policy Evaluation

arXiv:2412.08052v2 Announce Type: replace Abstract: Off-policy evaluation (OPE) is critical for applying contextual bandit algorithms to high-stakes decision-making settings such as healthcare, where

safetyarxiv-cs-lg

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Chance-Constrained MPPI under State and Dynamic Object Prediction Uncertainty and the Evaluation of Collision Risk Calibration

DGX agent

arXiv:2605.28330v1 Announce Type: new Abstract: Chance-constrained Model Predictive Path Integral (MPPI) control is increasingly adopted for navigation in dynamic environments to explicitly bound coll

safetyarxiv-cs-ro

28 May 2026

CIRF: Tokenizing Chain-of-Thoughts into Reusable Functional Units for Efficient Latent Reasoning in Large Language Models

arXiv:2605.28292v1 Announce Type: new Abstract: Implicit Chain-of-Thought (CoT) reduces the inference cost of large language models by internalizing the explicit rationales. However, existing approach

safetyarxiv-cs-cl

CiteCheck: Retrieval-Grounded Detection of LLM Citation Hallucinations in Scientific Text

arXiv:2605.27700v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate scientific reports, but they can produce references that appear plausible while contain

Local Ai

CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models

arXiv:2605.28115v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face severe memory and latency bottlenecks due to high-resolution visual tokens. While current token reduction methods the

local-aiarxiv-cs-ai

ClinConsensus: A Physician-Calibrated Benchmark for Evaluating Clinical Rubric Coverage in Chinese Medical LLMs

model-releasesarxiv-cs-cl

arXiv:2603.02097v5 Announce Type: replace Abstract: Open-ended medical LLM evaluation remains weakly grounded in physician-calibrated coverage of clinically relevant response criteria, especially in l

ClothTransformer: Unified Latent-Space Transformers for Scalable Cloth Simulation

arXiv:2605.27852v1 Announce Type: cross Abstract: Unified and scalable Transformers have recently achieved remarkable success in modeling diverse phenomena traditionally associated with computer graph

CogPortrait: Fine-Grained Eye-Region Control in Portrait Animation via Hierarchical Agent Planning

arXiv:2605.28056v1 Announce Type: new Abstract: Portrait animation methods have achieved substantial visual quality and lip synchronization, but fine-grained manipulation of the eye region still faces

CogVLA: Cognition-Aligned Vision-Language-Action Model via Instruction-Driven Routing & Sparsification

arXiv:2508.21046v3 Announce Type: replace Abstract: Recent Vision-Language-Action (VLA) models built on pre-trained Vision-Language Models (VLMs) require extensive post-training, resulting in high com

Compositional Text-to-Image Generation Via Region-aware Bimodal Direct Preference Optimization

arXiv:2605.28615v1 Announce Type: new Abstract: Despite the rapid progress of text-to-image (T2I) models, generating images that accurately reflect complex compositional prompts (covering attribute bi

Con-DSO: Learning Short-Horizon Consistency Priors for RGB-D Direct Sparse Odometry

arXiv:2605.27952v1 Announce Type: new Abstract: Visual odometry (VO) is a fundamental component in robotics and augmented reality. RGB-D direct VO benefits from metric depth measurements, but it can d

ConRAG: Consensus-Driven Multi-View Retrieval for Multi-Hop Question Answering

model-releasesarxiv-cs-cl

arXiv:2605.28093v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) has emerged as a promising paradigm for enhancing large language models (LLMs) on multi-hop question answering (QA)

CRaFT: Circuit-Guided Refusal Feature Selection via Cross-Layer Transcoders

arXiv:2604.01604v2 Announce Type: replace Abstract: While modern LLMs are aligned to refuse harmful requests, it is essential to understand the underlying mechanistic basis of this refusal behavior fo

Cross-Modal Action Recognition in Egocentric Video Using Mamba: Integrating RGB and Hand Skeleton Streams via CLS Token Fusion Strategies

arXiv:2605.24302v2 Announce Type: replace Abstract: Egocentric action recognition is a challenging task due to erratic camera motion, frequent hand occlusion, and the difficulty of maintaining consist

CubePart: An Open-Vocabulary Part-Controllable 3D Generator

arXiv:2605.28763v1 Announce Type: new Abstract: Interactive 3D assets used in games and simulation are typically decomposed into specific semantic parts to support animation, physics, and scripted beh

researcharxiv-cs-ai

CyberJurors: A Multi-Agent Simulation Task for E-Commerce Disputes Verdict

arXiv:2605.28369v1 Announce Type: new Abstract: E-commerce platforms have begun recruiting crowdsourced jurors to adjudicate massive volumes of transaction disputes. Unlike formal legal judgment, E-co

Agents

Cyclical Entropy Eruption: Entropy Dynamics in Agent Reinforcement Learning

arXiv:2605.27954v1 Announce Type: new Abstract: Agentic large language models are increasingly used to solve real-world tasks by reasoning over goals, invoking tools, and interacting with external env

agentsarxiv-cs-lg

Tutorials

D^2Turb: Depth-Aware Simulation and Decoupled Learning for Single-Frame Atmospheric Turbulence Mitigation

arXiv:2605.27460v1 Announce Type: new Abstract: Single-frame atmospheric turbulence mitigation is inherently ill-posed due to spatially varying blur coupled with non-rigid geometric distortion. Existi

tutorialsarxiv-cs-cv

Debate with Images: Detecting Deceptive Behaviors in Multimodal Large Language Models

arXiv:2512.00349v2 Announce Type: replace Abstract: Are frontier AI systems becoming more capable? Certainly. Yet such progress is not an unalloyed blessing but rather a Trojan horse: behind their per

DebFilter: Eradicating Biases Stashed in Value

arXiv:2605.28167v1 Announce Type: new Abstract: Text-to-image diffusion models, which are theoretically equivalent to score-based generative models, generate images through a multi-step denoising proc

Decision-focused learning for optimal PV-Battery scheduling

arXiv:2605.28340v1 Announce Type: cross Abstract: The use of residential photovoltaics has increased dramatically in recent years. With battery systems becoming more affordable, the optimal operation

Decoupled Training with Local Reinforcement Fine-Tuning in Federated Learning

arXiv:2605.27900v1 Announce Type: new Abstract: Federated Learning (FL) with pre-trained Vision-Language Models (VLMs) has emerged as a promising paradigm for various downstream tasks. By leveraging i

Decoupling Variance and Scale-Invariant Updates in Adaptive Gradient Descent for Unified Vector and Matrix Optimization

arXiv:2602.06880v2 Announce Type: replace Abstract: Adaptive methods like Adam have become the extit{de facto} standard for large-scale vector and Euclidean optimization due to their coordinate-wise a

Local Ai

DeepC4: Deep Conditional Census-Constrained Clustering for Large-scale Multitask Spatial Disaggregation of Urban Morphology

arXiv:2507.22554v3 Announce Type: replace Abstract: To understand our global progress for sustainable development and disaster risk reduction in many developing economies, two recent major initiatives

local-aiarxiv-cs-lg

Delay-Aware Reinforcement Learning for Highway On-Ramp Merging under Stochastic Communication Latency

arXiv:2403.11852v5 Announce Type: replace-cross Abstract: Delayed and partially observable state information poses significant challenges for reinforcement learning (RL)-based control in real-world au

DenoiseRL: Bootstrapping Reasoning Models to Recover from Noisy Prefixes

arXiv:2605.28421v1 Announce Type: new Abstract: Reinforcement learning has become a central paradigm for advancing reasoning in large language models, yet most existing methods still depend on stronge

Density-aware Sample-specific Attack

arXiv:2605.27809v1 Announce Type: new Abstract: Despite recent progress in backdoor attacks, existing methods remain susceptible to post-training defenses that erase the backdoor through fine-tuning o

Agents

Detect by Yourself: Self-Designing Agentic Workflows for Few-Shot Graph Anomaly Detection

arXiv:2605.27470v1 Announce Type: cross Abstract: Graph anomaly detection aims to identify anomaly nodes in attributed graphs and plays an important role in real-world applications. However, existing

agentsarxiv-cs-ai

Detection Without Correction: A Two-Parameter Decomposition of Multi-Stage LLM Pipelines

arXiv:2605.27559v1 Announce Type: cross Abstract: Multi-stage LLM pipelines that perform multi-agent debate, intrinsic self-correction, or retrieval-augmented verification exhibit puzzling aggregate b

Differentiable Model Predictive Safety for Heterogeneous Mobility at Urban Intersections

arXiv:2605.27418v1 Announce Type: cross Abstract: The imminent integration of autonomous vehicles and mobile robots in urban settings presents a critical safety challenge for future intelligent transp

safetyarxiv-cs-ro

Diffusion Large Language Models for Visual Speech Recognition

arXiv:2605.28456v1 Announce Type: new Abstract: Existing Visual Speech Recognition (VSR) systems commonly rely on left-to-right autoregressive decoding, which can force premature decisions on visually

Dimensionality Reduction for Robust Federated Learning: A Theoretical Analysis and Convergence Guarantee

model-releasesarxiv-cs-lg

arXiv:2605.28335v1 Announce Type: new Abstract: Federated Learning (FL) enables multiple clients to collaboratively train models without sharing raw data, but it is highly vulnerable to Byzantine atta

DisasterBench: Benchmarking LLM Planning under Typed Tool Interface Constraints

model-releasesarxiv-cs-cl

arXiv:2605.27957v1 Announce Type: new Abstract: Disasters cause severe societal impacts, demanding rapid coordination of heterogeneous AI tools, from satellite analysis to flood prediction and damage

Local Ai

Dual-branch Distilled Transformer for Efficient Asymmetric UAV Tracking

arXiv:2605.28018v1 Announce Type: new Abstract: Given the real-time demands of UAV tracking, many methods simplify the backbone to reduce computation, but this often weakens feature representation and

local-aiarxiv-cs-cv

Dynamic Topic Modeling with a Higher-Order Hypergraphical Representation

arXiv:2605.28269v1 Announce Type: new Abstract: Dynamic topic modeling is widely used to analyze evolving trends in scientific literature, medical records, and social media. Traditional topic models r

Efficient Pre-Training of LLMs through Truncated SVD Layers

arXiv:2605.28573v1 Announce Type: cross Abstract: The massive scaling of Large Language Models (LLMs) has made pretraining increasingly cost-prohibitive. While low-rank representation and orthonormal

EgoBench: An Interactive Egocentric Multimodal Benchmark for Tool-Using Agents

arXiv:2605.27820v1 Announce Type: new Abstract: As AI agents increasingly operate in open, real-world environments, they require a deep synergy of multimodal perception, tool invocation with multi-hop

EgoRelight: Egocentric Human Capture and Illumination Recovery for Relightable and Photoreal Avatar Rendering

arXiv:2605.28401v1 Announce Type: new Abstract: Mixed Reality (MR) headsets promise a future of immersive telepresence where virtual humans blend indistinguishably into real or virtual surroundings. A

Emerging Extrinsic Dexterity in Cluttered Scenes via Dynamics-aware Policy Learning

arXiv:2603.09882v2 Announce Type: replace-cross Abstract: Extrinsic dexterity leverages environmental contact to overcome the limitations of prehensile manipulation. However, achieving such dexterity

Enhancing Trustworthy GUI Grounding via Self-Critiqued Reinforcement Learning

arXiv:2510.27266v2 Announce Type: replace Abstract: Autonomous graphical user interface (GUI) agents rely on accurate GUI grounding, which maps language instructions to on-screen coordinates, to execu

EntroAD: Structural Entropy-Guided Prompt Adaptation for Zero-Shot Anomaly Detection

arXiv:2605.28630v1 Announce Type: new Abstract: Zero-Shot Anomaly Detection (ZSAD) aims to detect anomalies in unseen domains without target-domain adaptation. Recent CLIP-based methods have shown pro

Escape the Language Prior: Mitigating Late-Stage Modality Collapse in Audio Reasoning via Modality-Aware Policy Optimization

arXiv:2605.27741v1 Announce Type: new Abstract: Audio and omni-modal large language models exhibit impressive cross-modal reasoning capabilities. However, applying standard reinforcement learning post

safetyarxiv-cs-cl

EVADE-Bench: Multimodal Benchmark for Evaluating and Enhancing Evasive Content Detection

arXiv:2505.17654v4 Announce Type: replace-cross Abstract: E-commerce platforms increasingly rely on Large Language Models (LLMs) and Vision Language Models (VLMs) to detect illicit or misleading produ

Evaluating the Feasibility of Inferring Dietary Behavior Change Receptivity from Egocentric Images of Eating Environment

arXiv:2605.27950v1 Announce Type: new Abstract: Accurately assessing dietary behavior change receptivity is essential for designing effective just-in-time adaptive interventions (JITAIs) that promote

Evolving and Detecting Multi-Turn Deception using Geometric Signatures

arXiv:2605.27671v1 Announce Type: cross Abstract: Safety defenses for large language models (LLMs) are typically trained and evaluated on single-turn prompts, yet real attacks often unfold as indirect

safetyarxiv-cs-lg

Evolving Dataflow to process massive datasets for machine learning

model-releasesgoogle-cloud-ai

Google created MapReduce more than 20 years ago to solve the scaling problems in data processing that the then young company was running into. The AI era that we are in now demands efficient, large-sc

EvoSpec: Evolving Speculative Decoding via Real-Time Vocabulary and Parameter AdaptationTarget

arXiv:2605.27390v1 Announce Type: cross Abstract: Speculative decoding accelerates Large Language Model inference via a draft-then-verify paradigm, yet the output projection layer becomes a bottleneck

Exploratory Experience Shapes the Geometry of Predictive Representations

model-releasesarxiv-cs-lg

arXiv:2605.27929v1 Announce Type: cross Abstract: Active sensing links behavior and learning through an action-perception loop: actions determine the observations used to update internal predictive mo