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Earlier sources: Fusion
This energy thread follows fusion through original research, public projects, and source reports. Read the evidence below to see which developments are represented in SYMTRI’s archive.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗129 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
A trustworthy evidential transformer with linear fusion and Gram-matrix distillation for efficient optic disc and cup segmentation ↗
Accurate glaucoma screening relies on the vertical cup-to-disc ratio (VCDR), but automation remains challenging. A critical trade-off between computational efficiency, segmentation accuracy, and model trustworthiness hinders clinical deployment. Vision Transformers offer global context but suffer from quadratic complexity ( O ( N 2 ) ), while standard Convolutional Neural Networks lack explicit mechanisms for uncertainty quantification (UQ). To bridge this gap, we propose EviG-Former (Evidential Gram Transformer), a highly efficient student network trained via Teacher-Student distillation. Our…
- OpenAlex · Published · First archived
EDAFNet: efficient dual attention fusion network via multi-exposure image for HDR reconstruction ↗
Abstract High Dynamic Range (HDR) reconstruction from multi-exposure Low Dynamic Range (LDR) images requires recovering a wide luminance range while preserving details in bright and dark regions under motion and exposure misalignment. High reconstruction fidelity, however, often comes with increased computational complexity. This paper presents the Efficient Dual Attention Fusion Network (EDAFNet), which combines CBAM-guided initialization, hierarchical local and global attention for cross-exposure alignment and fusion, and a lightweight refinement module based on depthwise separable convoluti…
- OpenAlex · Published · First archived
ContractShield: Bridging semantic-structural gaps via hierarchical cross-modal fusion for multi-label vulnerability detection in obfuscated smart contracts ↗
Smart contracts are increasingly targeted by adversaries employing obfuscation techniques such as bogus code injection and control-flow manipulation to evade vulnerability detection. Existing multimodal methods often process semantic, temporal, and structural features in isolation and fuse them using simple strategies such as concatenation. This limits cross-modal interaction and weakens robustness when one modality is obfuscated. To address these challenges, we propose ContractShield, a multimodal framework with a three-stage hierarchical fusion mechanism. The first stage refines each modalit…
- OpenAlex · Published · First archived
Multimodal Fusion‐Based POI Recommendation With Consumer Equilibrium Guidance ↗
ABSTRACT Point of interest (POI) recommendation services have gained widespread adoption in various consumer fields. However, existing POI recommendation methods often neglect the intrinsic logic of consumer behaviors and multimodal data fusion analysis. To fill this research gap, this paper proposes a multimodal fusion‐Based POI recommendation method with consumer equilibrium guidance. This method considers different data modalities such as graphs, time series, images, text, and so forth, and draws inspiration from consumer equilibrium and diminishing marginal utility theories to simulate the…
- OpenAlex · Published · First archived
S2DFusion: a statistical and scale difference attention network for infrared and visible image fusion ↗
Infrared and visible image fusion aims to integrate cross-modal complementary information for comprehensive all-weather scene perception. However, existing methods often fail to effectively decouple background noise from modality-specific salient features, leading to contrast degradation, diminished thermal target prominence, and the loss of fine texture details in the fused images. To address these limitations, we propose S2DFusion, a novel statistical and scale-differential attention network that constructs a “difference-oriented” explicit decoupling and fusion paradigm. Specifically, the in…
- OpenAlex · Published · First archived
Development of a UV-Responsive Fusion Peptide Combining a Cell-Penetrating and a Mitochondria-Targeting Peptide to Suppress Intracellular Off-Target Effects ↗
Abstract Modification of plant mitochondria has attracted increasing attention as a strategy for developing highly productive crops, driving efforts to achieve efficient mitochondrial delivery of cargos. Mitochondria-targeting gene carriers with a strong cell-penetrating ability have been shown to deliver plasmid DNA into plant mitochondria, but this ability can reduce mitochondrial selectivity through nonspecific interaction with intracellular membranes. Herein, we developed a fusion peptide in which a mitochondria-targeting peptide was linked to a cell-penetrating peptide via an ultraviolet…
- arXiv · Published · First archived
FuseReg: Regularizing Layer Fusion Mitigates the Reconstruction-Generation Gap in Representation Autoencoders ↗
Representation autoencoders (RAEs) reuse features from a pretrained visual encoder as reconstruction and diffusion latents, integrating strong visual representations into image generation. However, RAEs still need to decide which encoder layers form the shared latent space for the generator and pixel decoder. This choice involves a trade-off. Shallower layers tend to preserve fine pixel details better, while deeper layers tend to yield better generation metrics. A fixed heuristic layer fusion therefore couples two stages that benefit from different information. We introduce FuseReg, which repl…
- arXiv · Published · First archived
Statistical Foundations for a Google Play User-Review Sentiment Index: Signal Fusion, Shrinkage, Distributional Validation, and Dynamic Smoothing ↗
We develop a statistically explicit sentiment index for Google Play user reviews and establish the mathematical results supporting its construction. Normalized star ratings and text-sentiment scores are treated as noisy measures of latent review valence and fused by covariance-aware inverse-variance weighting. Review-level estimates are aggregated with bounded helpfulness and recency weights, then shrunk toward a population mean using estimated precision rather than an arbitrary review-count threshold. App-level rating histograms provide a distributional diagnostic for samples returned under d…
- arXiv · Published · First archived
Impact of magnetic drift configuration on the edge radial electric field in the TCV tokamak ↗
The edge radial electric ($E_r$) in the Tokamak à Configuration Variable (TCV) is compared in matched L-mode discharges with opposite ion magnetic drift directions (favorable versus unfavorable $B \! \times \! \nabla B$ configurations). As previously reported on the WEST and AUG tokamaks, the $E_r$ profile---measured by Doppler backscattering (DBS)---exhibits a "well" just inside the separatrix in the favorable drift case, which is absent or less pronounced in the unfavorable counterpart. This observation holds over a broad range of plasma conditions, notably also in Ohmic discharges with near…
- arXiv · Published · First archived
ChronoFuseGS: Multi-Temporal Gaussian Fusion with Per-Splat Persistence and Change Visualization ↗
Reconstructing environments where parts of the scene change between captured image sets poses a challenge for 3D scene reconstruction. We present ChronoFuseGS, a multi-temporal Gaussian Splatting approach that addresses this issue by taking multiple separately trained Gaussian Splatting models, each representing a distinct timestep and partially overlapping in geographic coverage, and merging them into a single combined model. By allowing Gaussians from one timestep to contribute to the reconstruction at other timesteps, our approach leverages data across all captured timesteps to refine persi…
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How to assess evidence about Fusion
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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