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DriveAgent-R1: Advancing VLM-based Autonomous Driving with Active Perception and Hybrid Thinking

arXiv:2507.20879v3 Announce Type: replace Abstract: The advent of Vision-Language Models (VLMs) has significantly advanced end-to-end autonomous driving, demonstrating powerful reasoning abilities for

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Safety

Driving in Corner Case: A Real-World Adversarial Closed-Loop Evaluation Platform for End-to-End Autonomous Driving

DGX agent

arXiv:2512.16055v2 Announce Type: replace Abstract: Safety-critical corner cases, difficult to collect in the real world, are crucial for evaluating end-to-end autonomous driving. Adversarial interact

safetyarxiv-cs-cv

21 Apr 2026

Driving risk emerges from the required two-dimensional joint evasive acceleration

arXiv:2604.17841v1 Announce Type: new Abstract: Most autonomous driving safety benchmarks use time-to-collision (TTC) to assess risk and guide safe behaviour. However, TTC-based methods treat risk as

safetyarxiv-cs-ro

DSA-CycleGAN: A Domain Shift Aware CycleGAN for Robust Multi-Stain Glomeruli Segmentation

arXiv:2604.18368v1 Announce Type: new Abstract: A key challenge in segmentation in digital histopathology is inter- and intra-stain variations as it reduces model performance. Labelling each stain is

DSH-Bench: A Difficulty- and Scenario-Aware Benchmark with Hierarchical Subject Taxonomy for Subject-Driven Text-to-Image Generation

arXiv:2603.08090v2 Announce Type: replace Abstract: Significant progress has been achieved in subject-driven text-to-image (T2I) generation, which aims to synthesize new images depicting target subjec

Dual Alignment Between Language Model Layers and Human Sentence Processing

arXiv:2604.18563v1 Announce Type: new Abstract: A recent study (Kuribayashi et al., 2025) has shown that human sentence processing behavior, typically measured on syntactically unchallenging construct

safetyarxiv-cs-cl

Agents

Dual-Anchoring: Addressing State Drift in Vision-Language Navigation

arXiv:2604.17473v1 Announce Type: new Abstract: Vision-Language Navigation(VLN) requires an agent to navigate through 3D environments by following natural language instructions. While recent Video Lar

agentsarxiv-cs-cv

Dual-End Consistency Model

arXiv:2602.10764v2 Announce Type: replace Abstract: The slow iterative sampling nature remains a major bottleneck for the practical deployment of diffusion and flow-based generative models. While cons

Dual Strategies for Test-Time Adaptation

arXiv:2604.17542v1 Announce Type: new Abstract: Conventional test-time adaptation (TTA) approaches typically adapt the model using only a small fraction of test samples, often those with low-entropy p

Dual-stream Spatio-Temporal GCN-Transformer Network for 3D Human Pose Estimation

arXiv:2604.17688v1 Announce Type: new Abstract: 3D human pose estimation is a classic and important research direction in the field of computer vision. In recent years, Transformer-based methods have

Duality for the Adversarial Total Variation

arXiv:2604.18540v1 Announce Type: cross Abstract: Adversarial training of binary classifiers can be reformulated as regularized risk minimization involving a nonlocal total variation. Building on this

DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabularies

arXiv:2503.14324v3 Announce Type: replace-cross Abstract: The differing representation spaces required for visual understanding and generation pose a challenge in unifying them within the autoregressi

researcharxiv-cs-cl

DuConTE: Dual-Granularity Text Encoder with Topology-Constrained Attention for Text-attributed Graphs

arXiv:2604.17411v1 Announce Type: new Abstract: Text-attributed graphs integrate semantic information of node texts with topological structure, offering significant value in various applications such

DuQuant++: Fine-grained Rotation Enhances Microscaling FP4 Quantization

arXiv:2604.17789v1 Announce Type: cross Abstract: The MXFP4 microscaling format, which partitions tensors into blocks of 32 elements sharing an E8M0 scaling factor, has emerged as a promising substrat

Agents

DVAR: Adversarial Multi-Agent Debate for Video Authenticity Detection

arXiv:2604.16987v1 Announce Type: new Abstract: The rapid evolution of video generation technologies poses a significant challenge to media forensics, as conventional detection methods often fail to g

agentsarxiv-cs-cv

Dynamic Emotion and Personality Profiling for Multimodal Deception Detection

arXiv:2604.17037v1 Announce Type: new Abstract: Deception detection is of great significance for ensuring information security and conducting public opinion analysis, with personality factors and emot

safetyarxiv-cs-cl

Dynamic Eraser for Guided Concept Erasure in Diffusion Models

arXiv:2604.16483v1 Announce Type: new Abstract: Concept erasure in Text-To-Image (T2I) diffusion models is vital for safe content generation, but existing inference-time methods face significant limit

Dynamic Risk Assessment by Bayesian Attack Graphs and Process Mining

arXiv:2604.18080v1 Announce Type: cross Abstract: While attack graphs are useful for identifying major cybersecurity threats affecting a system, they do not provide operational support for determining

Dynamic Visual-semantic Alignment for Zero-shot Learning with Ambiguous Labels

arXiv:2604.17710v1 Announce Type: new Abstract: Zero-shot learning (ZSL) aims to recognize unseen classes without visual instances. However, existing methods usually assume clean labels, overlooking r

safetyarxiv-cs-cv

DynaWeb: Model-Based Reinforcement Learning of Web Agents

arXiv:2601.22149v2 Announce Type: replace Abstract: The development of autonomous web agents, powered by Large Language Models (LLMs) and reinforcement learning (RL), represents a significant step tow

safetyarxiv-cs-cl

E2E-GMNER: End-to-End Generative Grounded Multimodal Named Entity Recognition

arXiv:2604.17319v1 Announce Type: cross Abstract: Grounded Multimodal Named Entity Recognition (GMNER) aims to jointly identify named entity mentions in text, predict their semantic types, and ground

researcharxiv-cs-cl

E2E-WAVE: End-to-End Learned Waveform Generation for Underwater Video Multicasting

arXiv:2604.17047v1 Announce Type: cross Abstract: We present E2E-WAVE, the first end-to-end learned waveform generation system for underwater video multicasting. Acoustic channels exhibit 20--46% bit

E3VS-Bench: A Benchmark for Viewpoint-Dependent Active Perception in 3D Gaussian Splatting Scenes

arXiv:2604.17969v1 Announce Type: new Abstract: Visual search in 3D environments requires embodied agents to actively explore their surroundings and acquire task-relevant evidence. However, existing v

Tutorials

Early life may have breathed oxygen earlier than believed

Around 2.3 billion years ago, a pivotal period known as the Great Oxidation Event set the evolutionary course for oxygen-breathing life on Earth. But MIT geobiologists and colleagues have found eviden

tutorialsmit-tech-review

EarthSight: A Distributed Framework for Low-Latency Satellite Intelligence

arXiv:2511.10834v3 Announce Type: replace Abstract: Low-latency delivery of satellite imagery is essential for time-critical applications such as disaster response, intelligence, and infrastructure mo

EAST: Early Action Prediction Sampling Strategy with Token Masking

arXiv:2604.18367v1 Announce Type: new Abstract: Early action prediction seeks to anticipate an action before it fully unfolds, but limited visual evidence makes this task especially challenging. We in

EasyVideoR1: Easier RL for Video Understanding

arXiv:2604.16893v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has demonstrated remarkable effectiveness in improving the reasoning capabilities of large languag

EchoChain: A Full-Duplex Benchmark for State-Update Reasoning Under Interruptions

arXiv:2604.16456v1 Announce Type: new Abstract: Real-time voice assistants must revise task state when users interrupt mid-response, but existing spoken-dialog benchmarks largely evaluate turn-based i

eCP: Equivariant Conformal Prediction with pre-trained models

arXiv:2602.03986v2 Announce Type: replace Abstract: Conformal prediction, a post-hoc, distribution-free, finite-sample method of uncertainty quantification that offers formal coverage guarantees under

EdgeVTP: Exploration of Latency-efficient Trajectory Prediction for Edge-based Embedded Vision Applications

arXiv:2604.16783v1 Announce Type: new Abstract: Vehicle trajectory prediction is central to highway perception, but deployment on roadside edge devices necessitates bounded, deterministic end-to-end l

Applications

Edit Fidelity Field: Semantics-Aware Region Isolation for Training-Free Scene Text Editing

arXiv:2604.17500v1 Announce Type: new Abstract: Scene text editing (STE) has achieved remarkable progress in accurately rendering target text through diffusion-based methods. However, we identify a cr

applicationsarxiv-cs-cv

EditVerse: Unifying Image and Video Editing and Generation with In-Context Learning

arXiv:2509.20360v3 Announce Type: replace Abstract: Recent advances in foundation models highlight a clear trend toward unification and scaling, showing emergent capabilities across diverse domains. W

Tutorials

EduRABSA: An Education Review Dataset for Aspect-based Sentiment Analysis Tasks

arXiv:2508.17008v2 Announce Type: replace Abstract: Every year, most educational institutions seek and receive an enormous volume of text feedback from students on courses, teaching, and overall exper

tutorialsarxiv-cs-cl

EEG-Based Emergency Braking Intensity Prediction Using Blind Source Separation

arXiv:2604.18220v1 Announce Type: cross Abstract: Electroencephalography (EEG) signals have been promising for long-term braking intensity prediction but are prone to various artifacts that limit thei

Efficient Diffusion Models under Nonconvex Equality and Inequality constraints via Landing

arXiv:2604.17838v1 Announce Type: new Abstract: Generative modeling within constrained sets is essential for scientific and engineering applications involving physical, geometric, or safety requiremen

safetyarxiv-cs-lg

Efficient Federated RLHF via Zeroth-Order Policy Optimization

arXiv:2604.17747v1 Announce Type: new Abstract: This paper considers reinforcement learning from human feedback in a federated learning setting with resource-constrained agents, such as edge devices.

safetyarxiv-cs-lg

Efficient Inference for Coupled Hidden Markov Models in Continuous Time and Discrete Space

arXiv:2510.12916v2 Announce Type: replace-cross Abstract: Systems of interacting continuous-time Markov chains are a powerful model class, but inference is typically intractable in high dimensional se

Efficient Low-Resource Language Adaptation via Multi-Source Dynamic Logit Fusion

arXiv:2604.18106v1 Announce Type: new Abstract: Adapting large language models (LLMs) to low-resource languages (LRLs) is constrained by the scarcity of task data and computational resources. Although

researcharxiv-cs-cl

Efficient Task Adaptation in Large Language Models via Selective Parameter Optimization

arXiv:2604.17051v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated excellent performance in general language understanding, generation and other tasks. However, when fine-t

Ego-InBetween: Generating Object State Transitions in Ego-Centric Videos

arXiv:2604.17749v1 Announce Type: new Abstract: Understanding physical transformation processes is crucial for both human cognition and artificial intelligence systems, particularly from an egocentric

EgoSound: Benchmarking Sound Understanding in Egocentric Videos

arXiv:2602.14122v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have recently achieved remarkable progress in vision-language understanding. Yet, human perception is inher

Applications

EgoWalk: A Multimodal Dataset for Robot Navigation in the Wild

arXiv:2505.21282v2 Announce Type: replace Abstract: Data-driven navigation algorithms are critically dependent on large-scale, high-quality real-world data collection for successful training and robus

applicationsarxiv-cs-ro

Eluder dimension: localise it!

arXiv:2601.09825v2 Announce Type: replace Abstract: We establish a lower bound on the eluder dimension of generalised linear model classes, showing that standard eluder dimension-based analysis cannot

Embedding Arithmetic: A Lightweight, Tuning-Free Framework for Post-hoc Bias Mitigation in Text-to-Image Models

arXiv:2604.18167v1 Announce Type: new Abstract: Modern text-to-image (T2I) models amplify harmful societal biases, challenging their ethical deployment. We introduce an inference-time method that reli

EmbodiedHead: Real-Time Listening and Speaking Avatar for Conversational Agents

arXiv:2604.17211v1 Announce Type: new Abstract: We present EmbodiedHead, a speech-driven talking-head framework that equips LLMs with real-time visual avatars for conversation. A practical embodied av

EmbodiedLGR: Integrating Lightweight Graph Representation and Retrieval for Semantic-Spatial Memory in Robotic Agents

model-releasesarxiv-cs-ro

arXiv:2604.18271v1 Announce Type: new Abstract: As the world of agentic artificial intelligence applied to robotics evolves, the need for agents capable of building and retrieving memories and observa

Applications

EmbodiTTA: Resource-Efficient Test-Time Adaptation for Embodied Visual Systems

arXiv:2505.00986v2 Announce Type: replace-cross Abstract: Continual Test-time adaptation (CTTA) continuously adapts the deployed model on every incoming batch of data. While achieving optimal accuracy

applicationsarxiv-cs-cv

Emergency Stopping for Liquid-manipulating Robots

arXiv:2604.16667v1 Announce Type: new Abstract: Manipulating open liquid containers is challenging because liquids are highly sensitive to vessel accelerations and jerks. Although spill-free liquid ma

safetyarxiv-cs-ro