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Beyond Loss Values: Robust Dynamic Pruning via Loss Trajectory Alignment

arXiv:2604.07306v1 Announce Type: cross Abstract: Existing dynamic data pruning methods often fail under noisy-label settings, as they typically rely on per-sample loss as the ranking criterion. This

safetyarxiv-cs-lg

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Beyond Mamba: Enhancing State-space Models with Deformable Dilated Convolutions for Multi-scale Traffic Object Detection

DGX agent

arXiv:2604.08038v1 Announce Type: new Abstract: In a real-world traffic scenario, varying-scale objects are usually distributed in a cluttered background, which poses great challenges to accurate dete

model-releasesarxiv-cs-cv

10 Apr 2026

Beyond Pedestrians: Caption-Guided CLIP Framework for High-Difficulty Video-based Person Re-Identification

arXiv:2604.07740v1 Announce Type: new Abstract: In recent years, video-based person Re-Identification (ReID) has gained attention for its ability to leverage spatiotemporal cues to match individuals a

researcharxiv-cs-cv

Beyond Pessimism: Offline Learning in KL-regularized Games

arXiv:2604.06738v1 Announce Type: cross Abstract: We study offline learning in KL-regularized two-player zero-sum games, where policies are optimized under a KL constraint to a fixed reference policy.

safetyarxiv-cs-lg

Beyond Social Pressure: Benchmarking Epistemic Attack in Large Language Models

arXiv:2604.07749v1 Announce Type: new Abstract: Large language models (LLMs) can shift their answers under pressure in ways that reflect accommodation rather than reasoning. Prior work on sycophancy h

Beyond Surface Artifacts: Capturing Shared Latent Forgery Knowledge Across Modalities

arXiv:2604.07763v1 Announce Type: new Abstract: As generative artificial intelligence evolves, deepfake attacks have escalated from single-modality manipulations to complex, multimodal threats. Existi

Beyond Surface Judgments: Human-Grounded Risk Evaluation of LLM-Generated Disinformation

arXiv:2604.06820v1 Announce Type: new Abstract: Large language models (LLMs) can generate persuasive narratives at scale, raising concerns about their potential use in disinformation campaigns. Assess

safetyarxiv-cs-ai

Beyond the Mean: Modelling Annotation Distributions in Continuous Affect Prediction

arXiv:2604.07198v1 Announce Type: new Abstract: Emotion annotation is inherently subjective and cognitively demanding, producing signals that reflect diverse perceptions across annotators rather than

Bi-level Heterogeneous Learning for Time Series Foundation Models: A Federated Learning Approach

arXiv:2604.06727v1 Announce Type: new Abstract: Heterogeneity in time series data is more pronounced than in vision or language, as temporal dynamics vary substantially across domains and tasks. Exist

Bi-Level Optimization for Single Domain Generalization

arXiv:2604.06349v1 Announce Type: cross Abstract: Generalizing from a single labeled source domain to unseen target domains, without access to any target data during training, remains a fundamental ch

Bi-Lipschitz Autoencoder With Injectivity Guarantee

arXiv:2604.06701v1 Announce Type: new Abstract: Autoencoders are widely used for dimensionality reduction, based on the assumption that high-dimensional data lies on low-dimensional manifolds. Regular

Bias Redistribution in Visual Machine Unlearning: Does Forgetting One Group Harm Another?

arXiv:2604.08111v1 Announce Type: cross Abstract: Machine unlearning enables models to selectively forget training data, driven by privacy regulations such as GDPR and CCPA. However, its fairness impl

safetyarxiv-cs-cv

Bird-Inspired Spatial Flapping Wing Mechanism via Coupled Linkages with Single Actuator

arXiv:2604.07677v1 Announce Type: new Abstract: Spatial single-loop mechanisms such as Bennett linkages offer a unique combination of one-degree-of-freedom actuation and nontrivial spatial trajectorie

researcharxiv-cs-ro

BiScale-GTR: Fragment-Aware Graph Transformers for Multi-Scale Molecular Representation Learning

arXiv:2604.06336v1 Announce Type: cross Abstract: Graph Transformers have recently attracted attention for molecular property prediction by combining the inductive biases of graph neural networks (GNN

BLaDA: Bridging Language to Functional Dexterous Actions within 3DGS Fields

arXiv:2604.08410v1 Announce Type: new Abstract: In unstructured environments, functional dexterous grasping calls for the tight integration of semantic understanding, precise 3D functional localizatio

researcharxiv-cs-cv

Blending Human and LLM Expertise to Detect Hallucinations and Omissions in Mental Health Chatbot Responses

arXiv:2604.06216v1 Announce Type: cross Abstract: As LLM-powered chatbots are increasingly deployed in mental health services, detecting hallucinations and omissions has become critical for user safet

Blind Refusal: Language Models Refuse to Help Users Evade Unjust, Absurd, and Illegitimate Rules

arXiv:2604.06233v1 Announce Type: new Abstract: Safety-trained language models routinely refuse requests for help circumventing rules. But not all rules deserve compliance. When users ask for help eva

Agents

Blockchain and AI: Securing Intelligent Networks for the Future

arXiv:2604.06323v2 Announce Type: cross Abstract: Blockchain and artificial intelligence (AI) are increasingly proposed together for securing intelligent networks, but the literature remains fragmente

agentsarxiv-cs-ai

Bootstrapping Sign Language Annotations with Sign Language Models

arXiv:2604.07606v1 Announce Type: new Abstract: AI-driven sign language interpretation is limited by a lack of high-quality annotated data. New datasets including ASL STEM Wiki and FLEURS-ASL contain

Brain3D: EEG-to-3D Decoding of Visual Representations via Multimodal Reasoning

arXiv:2604.08068v1 Announce Type: new Abstract: Decoding visual information from electroencephalography (EEG) has recently achieved promising results, primarily focusing on reconstructing two-dimensio

safetyarxiv-cs-cv

Break Me If You Can: Self-Jailbreaking of Aligned LLMs via Lexical Insertion Prompting

arXiv:2601.02670v2 Announce Type: replace Abstract: We introduce self-jailbreaking, a threat model in which an aligned LLM guides its own compromise. Unlike most jailbreak techniques, which oft

Bridging MRI and PET physiology: Untangling complementarity through orthogonal representations

arXiv:2604.07154v1 Announce Type: cross Abstract: Multimodal imaging analysis often relies on joint latent representations, yet these approaches rarely define what information is shared versus modalit

Applications

Bridging Natural Language and Microgrid Dynamics: A Context-Aware Simulator and Dataset

arXiv:2604.05429v2 Announce Type: replace-cross Abstract: Addressing the critical need for intelligent, context-aware energy management in renewable systems, we introduce the OpenCEM Simulator and Dat

applicationsarxiv-cs-ai

Bridging Theory and Practice in Crafting Robust Spiking Reservoirs

model-releasesarxiv-cs-lg

arXiv:2604.06395v1 Announce Type: new Abstract: Spiking reservoir computing provides an energy-efficient approach to temporal processing, but reliably tuning reservoirs to operate at the edge-of-chaos

Bridging Time and Space: Decoupled Spatio-Temporal Alignment for Video Grounding

arXiv:2604.08014v1 Announce Type: new Abstract: Spatio-Temporal Video Grounding requires jointly localizing target objects across both temporal and spatial dimensions based on natural language queries

local-aiarxiv-cs-cv

Broken by Default: A Formal Verification Study of Security Vulnerabilities in AI-Generated Code

arXiv:2604.05292v2 Announce Type: replace-cross Abstract: AI coding assistants are now used to generate production code in security-sensitive domains, yet the exploitability of their outputs remains u

BTC-LLM: Efficient Sub-1-Bit LLM Quantization via Learnable Transformation and Binary Codebook

arXiv:2506.12040v2 Announce Type: replace-cross Abstract: Binary quantization represents the most extreme form of compression, reducing weights to +/-1 for maximal memory and computational efficiency.

Busemann energy-based attention for emotion analysis in Poincare discs

arXiv:2604.06752v1 Announce Type: new Abstract: We present EmBolic - a novel fully hyperbolic deep learning architecture for fine-grained emotion analysis from textual messages. The underlying idea is

CAAP: Capture-Aware Adversarial Patch Attacks on Palmprint Recognition Models

arXiv:2604.06987v1 Announce Type: cross Abstract: Palmprint recognition is deployed in security-critical applications, including access control and palm-based payment, due to its contactless acquisiti

CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency

arXiv:2604.07286v1 Announce Type: cross Abstract: Autonomous vehicles deployed in remote environments typically rely on embedded processors, compact batteries, and lightweight sensors. These hardware

CAFP: A Post-Processing Framework for Group Fairness via Counterfactual Model Averaging

arXiv:2604.07009v1 Announce Type: new Abstract: Ensuring fairness in machine learning predictions is a critical challenge, especially when models are deployed in sensitive domains such as credit scori

safetyarxiv-cs-ai

Calibration of a neural network ocean closure for improved mean state and variability

model-releasesarxiv-cs-lg

arXiv:2604.06398v1 Announce Type: cross Abstract: Global ocean models exhibit biases in the mean state and variability, particularly at coarse resolution, where mesoscale eddies are unresolved. To add

CAMO: A Class-Aware Minority-Optimized Ensemble for Robust Language Model Evaluation on Imbalanced Data

arXiv:2604.07583v1 Announce Type: new Abstract: Real-world categorization is severely hampered by class imbalance because traditional ensembles favor majority classes, which lowers minority performanc

CAMotion: A High-Quality Benchmark for Camouflaged Moving Object Detection in the Wild

arXiv:2604.08287v1 Announce Type: new Abstract: Discovering camouflaged objects is a challenging task in computer vision due to the high similarity between camouflaged objects and their surroundings.

Can Vision Language Models Judge Action Quality? An Empirical Evaluation

arXiv:2604.08294v1 Announce Type: cross Abstract: Action Quality Assessment (AQA) has broad applications in physical therapy, sports coaching, and competitive judging. Although Vision Language Models

Agents

Can VLMs Unlock Semantic Anomaly Detection? A Framework for Structured Reasoning

arXiv:2510.18034v2 Announce Type: replace-cross Abstract: Autonomous driving systems remain critically vulnerable to the long-tail of rare, out-of-distribution semantic anomalies. While VLMs have emer

agentsarxiv-cs-ai

CASE: Cadence-Aware Set Encoding for Large-Scale Next Basket Repurchase Recommendation

model-releasesarxiv-cs-lg

arXiv:2604.06718v2 Announce Type: cross Abstract: Repurchase behavior is a primary signal in large-scale retail recommendation, particularly in categories with frequent replenishment: many items in a

CBM-Dual: A 65-nm Fully Connected Chaotic Boltzmann Machine Processor for Dual Function Simulated Annealing and Reservoir Computing

arXiv:2604.06808v1 Announce Type: cross Abstract: This paper presents CBM-Dual, the first silicon-proven digital chaotic dynamics processor (CDP) supporting both simulated annealing (SA) and reservoir

local-aiarxiv-cs-lg

ChangeBridge: Spatiotemporal Image Generation with Multimodal Controls for Remote Sensing

arXiv:2507.04678v3 Announce Type: replace Abstract: Spatiotemporal image generation is a highly meaningful task, which can generate future scenes conditioned on given observations. However, existing c

researcharxiv-cs-cv

Applications

Characterizing the Resilience and Sensitivity of Polyurethane Vision-Based Tactile Sensors

arXiv:2511.07797v2 Announce Type: replace Abstract: Vision-based tactile sensors (VBTSs) are a promising technology for robots, providing them with dense signals that can be translated into a multi-fa

applicationsarxiv-cs-ro

Chatbot-Based Assessment of Code Understanding in Automated Programming Assessment Systems

arXiv:2604.07304v1 Announce Type: cross Abstract: Large Language Models (LLMs) challenge conventional automated programming assessment because students can now produce functionally correct code withou

local-aiarxiv-cs-ai

Applications

ChemVLR: Prioritizing Reasoning in Perception for Chemical Vision-Language Understanding

arXiv:2604.06685v1 Announce Type: cross Abstract: While Vision-Language Models (VLMs) have demonstrated significant potential in chemical visual understanding, current models are predominantly optimiz

applicationsarxiv-cs-ai

CHiQPM: Calibrated Hierarchical Interpretable Image Classification

arXiv:2511.20779v2 Announce Type: replace Abstract: Globally interpretable models are a promising approach for trustworthy AI in safety-critical domains. Alongside global explanations, detailed local

local-aiarxiv-cs-lg

ChopGrad: Pixel-Wise Losses for Latent Video Diffusion via Truncated Backpropagation

arXiv:2603.17812v2 Announce Type: replace-cross Abstract: Recent video diffusion models achieve high-quality generation through recurrent frame processing where each frame generation depends on previo

Chunks as Arms: Multi-Armed Bandit-Guided Sampling for Long-Context LLM Preference Optimization

arXiv:2508.13993v2 Announce Type: replace Abstract: Long-context modeling is critical for a wide range of real-world tasks, including long-context question answering, summarization, and complex reason

ClawBench: Can AI Agents Complete Everyday Online Tasks?

arXiv:2604.08523v1 Announce Type: new Abstract: AI agents may be able to automate your inbox, but can they automate other routine aspects of your life? Everyday online tasks offer a realistic yet unso

Agents

ClawLess: A Security Model of AI Agents

arXiv:2604.06284v1 Announce Type: cross Abstract: Autonomous AI agents powered by Large Language Models can reason, plan, and execute complex tasks, but their ability to autonomously retrieve informat

agentsarxiv-cs-ai

ClawsBench: Evaluating Capability and Safety of LLM Productivity Agents in Simulated Workspaces

arXiv:2604.05172v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly deployed to automate productivity tasks (e.g., email, scheduling, document management), but evalu