arXiv AI
Aug 6
TwinIR: Coordinated Invisible Dual-Point Attacks on Online HD Map Construction
arXiv:2608. 04453v1 Announce Type: cross Abstract: Online HD map construction is critical to prediction and planning in autonomous driving.
Inference efficiency
Quantization, distillation, pruning and serving work aimed at the same accuracy for less memory, latency and money.
arXiv Machine Learning
Aug 6
Attention-Only White-Box Transformer via LeJEPA-Based Self-Supervised Pretraining
arXiv:2608. 04213v1 Announce Type: new Abstract: Existing studies on self-supervised learning for white-box networks typically decouple the derivation of white-box networks via optimization algorithms from self-supervised learning paradigms.
arXiv AI
Aug 6
CheMLFlow: An Open-Source Platform for Cheminformatics and Materials Informatics Applications
arXiv:2608. 04942v1 Announce Type: cross Abstract: CheMLFlow is an open-source platform for building and executing end-to-end, high-throughput, and agentic workflows for scientific and technological applications.
arXiv Machine Learning
Aug 6
Diverse and Plausible Algorithmic Recourse via Tractable Recourse Distributions
arXiv:2608. 04677v1 Announce Type: new Abstract: Algorithmic recourse seeks to help individuals reverse unfavorable automated decisions by recommending actionable changes that achieve a desired outcome.
arXiv Machine Learning
Aug 6
RiboSphere: Learning Unified and Efficient Representations of RNA Structures
arXiv:2603. 19636v2 Announce Type: replace Abstract: Accurate RNA structure modeling remains difficult because RNA backbones are highly flexible, non-canonical interactions are prevalent, and experimentally determined 3D structures are comparatively scarce.
arXiv Machine Learning
Aug 6
Reward Structure Shapes the Interaction Between Episodic Exploration and Neural Memory in Reinforcement Learning
arXiv:2608. 05111v1 Announce Type: new Abstract: In partially observable reinforcement learning, agents face a dual bottleneck: they must explore to encounter rewarding states and retain that experience in memory to optimize their policies.
arXiv AI
Aug 6
Tropical Algebraic Geometry for Neuronal Representations: An Arakelov-Green Measure Based Descriptor for Graph Learning
arXiv:2608. 04460v1 Announce Type: cross Abstract: The quantitative analysis of 3D neuronal morphologies requires capturing both graph topology and spatial geometry.
arXiv AI
Aug 6
Not Every Divergence Should Be Suppressed: Counterfactual Recoverability in On-Policy Distillation
arXiv:2608. 04408v1 Announce Type: cross Abstract: On-policy distillation (OPD) supervises student-visited trajectories, yet divergence-based rules cannot determine whether an erroneous prefix remains correctable.
arXiv AI
Aug 6
VQ-VAD: Vector-quantized Motion Representation Learning for Human-centric Video Anomaly Detection
arXiv:2608. 05069v1 Announce Type: cross Abstract: Video Anomaly Detection (VAD) is inherently challenging due to the scarcity of anomalies and the large visual variability in surveillance footage, including changes in lighting, viewpoint, and human appearance.
arXiv Machine Learning
Aug 6
Towards Understanding Gradient Flow Dynamics of Homogeneous Neural Networks Beyond the Origin
arXiv:2502. 15952v3 Announce Type: replace Abstract: Recent works exploring the training dynamics of homogeneous neural network weights under gradient flow with small initialization have established that in the early stages of training, the weights remain small and near the origin, but converge in direction.
arXiv AI
Aug 6
CSGen: A Multi-Domain Curvilinear Structure Generation Model via Hierarchical Multimodal Diffusion
arXiv:2608. 04655v1 Announce Type: cross Abstract: Curvilinear structure analysis is an important and fundamental task in multimedia.
arXiv AI
Aug 6
Recurrent Residual Quantization: A Progressive Multi-Precision Representation for LLMs
arXiv:2608. 04048v1 Announce Type: cross Abstract: Serving large language models (LLMs) under diverse deployment constraints requires flexible trade-offs between accuracy, memory footprint, and throughput.
arXiv AI
Aug 6
Instruction-Conditioned Exploration for Reinforcement Learning with Self-Distillation to an Unconditioned Policy
arXiv:2608. 02087v2 Announce Type: replace Abstract: Post-training Large Language Models (LLMs) with Reinforcement Learning (RL) has become an important tool for improving model capabilities, but the LLM action-space structure introduces challenges distinct from classical RL, with implications for inducing exploration.
arXiv Machine Learning
Aug 6
Understanding Fault Tolerance of Adversarially Robust Pruned Models
arXiv:2608. 04173v1 Announce Type: new Abstract: Deep neural networks (DNNs) deployed on resource-constrained neuromorphic hardware face three concurrent challenges: the need for model compression through pruning, vulnerability to adversarial input perturbations, and susceptibility to hardware-induced weight faults such as stuck-at-zero errors.
arXiv AI
Aug 6
Spend Bits Where Queries Look: KV Cache Vector Quantization with Attention-Preserving Transforms
arXiv:2608. 04074v1 Announce Type: cross Abstract: Long-context LLM decoding reads the key-value (KV) cache at every step.
arXiv AI
Aug 6
AFD-Ledger: Deployment Provisioning for Attention--FFN Disaggregation
arXiv:2608. 04502v1 Announce Type: cross Abstract: Attention--Feed-Forward Network (FFN) Disaggregation (AFD) is emerging as a promising architecture for serving Mixture-of-Experts (MoE) language models.
arXiv Machine Learning
Aug 6
DIVE: Dynamic Iterative Visual Evidence Construction for Efficient Vision-Language Models
arXiv:2608. 04496v1 Announce Type: cross Abstract: Visual inputs in vision-language models (VLMs) are often encoded into substantially longer token sequences than text, making visual tokens a major bottleneck for efficient inference.
arXiv AI
Aug 6
Interpreting GFlowNets for Drug Discovery: What probes can and cannot show
arXiv:2511. 19264v2 Announce Type: replace-cross Abstract: Generative Flow Networks (GFlowNets) construct molecules through sequential decisions, but their internal policies remain opaque, limiting adoption in drug discovery, where chemists need interpretable rationales for proposed structures.
arXiv AI
Aug 6
FinReportBench: Measuring and Improving Institution-Grade Financial Report Generation
arXiv:2608. 04374v1 Announce Type: cross Abstract: Large language models can produce fluent financial analysis, but fluency alone does not establish whether a report is suitable for institutional delivery.
arXiv AI
Aug 6
Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks
arXiv:2608. 04593v1 Announce Type: cross Abstract: Echo State Networks (ESNs) offer an efficient framework for temporal prediction, but their randomly initialized reservoirs are often over-parameterized and dynamically redundant.