Temporal Boundaries
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Quantum Photonic Time Crystals: From Temporal Boundaries to Floquet Light-Matter Interactions
arXiv:2605.30850v1 Announce Type: new Abstract: Photonic time crystals (PTCs) are temporally periodic media whose Floquet spectra can exhibit momentum gaps, parametric amplification, and effective non-Hermitian descriptions, making them an idealized setting for vacuum amplification and nonequilibrium light-matter dynamics. Their classical electrodynamics is now well developed; the quantum side is less so, and this focused review is an attempt to organize what exists. We trace that account...
Quantum Photonic Time Crystals: From Temporal Boundaries to Floquet Light-Matter Interactions
arXiv:2605.30850v2 Announce Type: replace Abstract: Photonic time crystals (PTCs) are temporally periodic media whose Floquet spectra can exhibit momentum gaps, parametric amplification, and effective non-Hermitian descriptions, making them an idealized setting for vacuum amplification and nonequilibrium light-matter dynamics. Their classical electrodynamics is now well developed; the quantum side is less so, and this focused review is an attempt to organize what exists. We trace that...
Deep reinforcement learning with spatial and temporal awareness for active boundary control of buoyancy-driven convection
arXiv:2606.06191v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) applied to thermal convection control consistently produces \textit{degenerate actuation}: wall-temperature policies whose outputs are saturated, pseudo-random, or spatially incoherent. Two compounding deficiencies are responsible: multilayer-perceptron policies that discard spatial flow structure, and memoryless policies that cannot distinguish self-induced flow changes from background evolution. Together they...
G-STAR: End-to-End Global Speaker-Tracking Attributed Recognition
arXiv:2603.10468v2 Announce Type: replace-cross Abstract: We study timestamped speaker-attributed automatic speech recognition (SA-ASR) for long-form, multi-party speech with overlap. In this setting, chunk-wise inference must preserve meeting-level speaker identity consistency while producing time-stamped, speaker-labeled transcripts. Prior Speech-LLM systems tend to prioritize either local diarization or global labeling, lacking the ability to jointly model fine-grained temporal boundaries...
BioVid: Autoregressive Video Generation with Biological Behavior Semantic Comprehension
arXiv:2606.08674v1 Announce Type: new Abstract: Existing video generation frameworks treat sequence duration as an externally prescribed parameter -- fixed frame counts or text prompts -- producing clips whose temporal boundaries are decoupled from the statistical structure of real behavioral data. This assumption is fundamentally misaligned with biological behavior, where action duration varies naturally across individuals and instances and is encoded in the data itself. We present BioVid,...
DRIFT: A Residual Flow Adapter for Decoding Continuous Outputs in Vision-Language Models
arXiv:2606.05758v1 Announce Type: new Abstract: Many modern vision-language models (VLMs) build on autoregressive decoding of discrete tokens. While text-based output interfaces enable scalable pretraining and strong zero-shot generalization across diverse tasks, they are poorly suited for problems that require precise continuous outputs, such as localizing temporal boundaries of events or generating robotic control actions.
Which Leakage Types Matter? A Quantitative Landscape Across 2,047 Benchmark Datasets
arXiv:2604.04199v2 Announce Type: replace Abstract: Twenty-eight within-subject counterfactual experiments across 2,047 iid tabular datasets, plus a boundary experiment on 129 temporal datasets, measure the severity of four data leakage classes in machine learning. Class I (estimation: fitting scalers on full data) is negligible: all nine conditions produce $|{\Delta}AUC| \leq 0.005$. Class II (selection: peeking, seed cherry-picking) is substantial: the measured effect is consistent with...
Sound Event Detection with Boundary-Aware Optimization and Inference
arXiv:2601.04178v2 Announce Type: replace-cross Abstract: Temporal detection problems appear in many fields including time-series estimation, activity recognition and sound event detection (SED). In this work, we propose a new approach to temporal event modeling by explicitly modeling event onsets and offsets, and by introducing boundary-aware optimization and inference strategies that substantially enhance temporal event detection. The presented methodology incorporates new temporal...
Temporal Evidence Routing with Structured Visual Evidence for TimeLogicQA
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OmniEgo-R$^2$: A Routed Reasoning Framework for the 1st Cross-Domain EgoCross Challenge at CVPR 2026
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