641
AI is reshaping banking—but not causing a jobs wipeout
Banking and finance headcounts remain largely stable, according to a Fortune report.
Kathleen P
552
VisionDirector: Vision-Language Guided Closed-Loop Refinement for Generative Image Synthesis
arXiv:2512.19243v1 Announce Type: new
Abstract: Generative models can now produce photorealistic imagery, yet they still struggle with the long, multi-goal prompts that professional designers issue. To expose this gap and better evaluate models' performance in real-world settings, we introduce Long…
Abstract: Generative models can now produce photorealistic imagery, yet they still struggle with the long, multi-goal prompts that professional designers issue. To expose this gap and better evaluate models' performance in real-world settings, we introduce Long…
Lilgski
431
Fraud Detection Through Large-Scale Graph Clustering with Heterogeneous Link Transformation
arXiv:2512.19061v1 Announce Type: new
Abstract: Collaborative fraud, where multiple fraudulent accounts coordinate to exploit online payment systems, poses significant challenges due to the formation of complex network structures. Traditional detection methods that rely solely on high-confidence id…
Abstract: Collaborative fraud, where multiple fraudulent accounts coordinate to exploit online payment systems, poses significant challenges due to the formation of complex network structures. Traditional detection methods that rely solely on high-confidence id…
Barrettfosterca
343
Transforming Data Management In EDA: Preparing For The AI Era
Ensuring data moves smoothly across multiple disciplines, tools, and globally distributed teams.
The post Transforming Data Management In EDA: Preparing For The AI Era appeared first on Semiconductor Engineering.
The post Transforming Data Management In EDA: Preparing For The AI Era appeared first on Semiconductor Engineering.
Chrisdang126
333
Self-Consistent Probability Flow for High-Dimensional Fokker-Planck Equations
arXiv:2512.19196v1 Announce Type: cross
Abstract: Solving high-dimensional Fokker-Planck (FP) equations is a challenge in computational physics and stochastic dynamics, due to the curse of dimensionality (CoD) and the bottleneck of evaluating second-order diffusion terms. Existing deep learning app…
Abstract: Solving high-dimensional Fokker-Planck (FP) equations is a challenge in computational physics and stochastic dynamics, due to the curse of dimensionality (CoD) and the bottleneck of evaluating second-order diffusion terms. Existing deep learning app…
Alessandro C
332
LLVM Considering An AI Tool Policy, AI Bot For Fixing Build System Breakage Proposed
Last week a request for comments (RFC) was issued around establishing an LLVM AI Tool Use Policy. The proposed policy would allow AI-assisted contributions to be made to this open-source compiler codebase but that there would need to be a "human in the loop" and the contributor versed enough to be a…
Schuylerrichardson
333
A Convolutional Neural Deferred Shader for Physics Based Rendering
arXiv:2512.19522v1 Announce Type: new
Abstract: Recent advances in neural rendering have achieved impressive results on photorealistic shading and relighting, by using a multilayer perceptron (MLP) as a regression model to learn the rendering equation from a real-world dataset. Such methods show pr…
Abstract: Recent advances in neural rendering have achieved impressive results on photorealistic shading and relighting, by using a multilayer perceptron (MLP) as a regression model to learn the rendering equation from a real-world dataset. Such methods show pr…
Unknown
321
No Pose at All: Self-Supervised Pose-Free 3D Gaussian Splatting from Sparse Views
arXiv:2508.01171v2 Announce Type: replace
Abstract: We introduce SPFSplat, an efficient framework for 3D Gaussian splatting from sparse multi-view images, requiring no ground-truth poses during training or inference. It employs a shared feature extraction backbone, enabling simultaneous prediction …
Abstract: We introduce SPFSplat, an efficient framework for 3D Gaussian splatting from sparse multi-view images, requiring no ground-truth poses during training or inference. It employs a shared feature extraction backbone, enabling simultaneous prediction …
Anholla
324
Overcoming Spectral Bias via Cross-Attention
arXiv:2512.18586v1 Announce Type: new
Abstract: Spectral bias implies an imbalance in training dynamics, whereby high-frequency components may converge substantially more slowly than low-frequency ones. To alleviate this issue, we propose a cross-attention-based architecture that adaptively reweigh…
Abstract: Spectral bias implies an imbalance in training dynamics, whereby high-frequency components may converge substantially more slowly than low-frequency ones. To alleviate this issue, we propose a cross-attention-based architecture that adaptively reweigh…
Mistymook
321
Shape it Up! Restoring LLM Safety during Finetuning
arXiv:2505.17196v3 Announce Type: replace
Abstract: Finetuning large language models (LLMs) enables user-specific customization but introduces critical safety risks: even a few harmful examples can compromise safety alignment. A common mitigation strategy is to update the model more strongly on exa…
Abstract: Finetuning large language models (LLMs) enables user-specific customization but introduces critical safety risks: even a few harmful examples can compromise safety alignment. A common mitigation strategy is to update the model more strongly on exa…
Schuylerrichardson
240
DTCCL: Disengagement-Triggered Contrastive Continual Learning for Autonomous Bus Planners
arXiv:2512.18988v1 Announce Type: new
Abstract: Autonomous buses run on fixed routes but must operate in open, dynamic urban environments. Disengagement events on these routes are often geographically concentrated and typically arise from planner failures in highly interactive regions. Such policy-…
Abstract: Autonomous buses run on fixed routes but must operate in open, dynamic urban environments. Disengagement events on these routes are often geographically concentrated and typically arise from planner failures in highly interactive regions. Such policy-…
Qwertass
232
Guard-GBDT: Efficient Privacy-Preserving Approximated GBDT Training on Vertical Dataset
arXiv:2507.20688v2 Announce Type: replace
Abstract: In light of increasing privacy concerns and stringent legal regulations, using secure multiparty computation (MPC) to enable collaborative GBDT model training among multiple data owners has garnered significant attention. Despite this, existing MP…
Abstract: In light of increasing privacy concerns and stringent legal regulations, using secure multiparty computation (MPC) to enable collaborative GBDT model training among multiple data owners has garnered significant attention. Despite this, existing MP…
Emmaelliott2888
222
Exploring Zero-Shot ACSA with Unified Meaning Representation in Chain-of-Thought Prompting
arXiv:2512.19651v1 Announce Type: new
Abstract: Aspect-Category Sentiment Analysis (ACSA) provides granular insights by identifying specific themes within reviews and their associated sentiment. While supervised learning approaches dominate this field, the scarcity and high cost of annotated data f…
Abstract: Aspect-Category Sentiment Analysis (ACSA) provides granular insights by identifying specific themes within reviews and their associated sentiment. While supervised learning approaches dominate this field, the scarcity and high cost of annotated data f…
Adam T
220
A Comprehensive Survey on Generative AI for Video-to-Music Generation
arXiv:2502.12489v2 Announce Type: replace-cross
Abstract: The burgeoning growth of video-to-music generation can be attributed to the ascendancy of multimodal generative models. However, there is a lack of literature that comprehensively combs through the work in this field. To fill this gap, this …
Abstract: The burgeoning growth of video-to-music generation can be attributed to the ascendancy of multimodal generative models. However, there is a lack of literature that comprehensively combs through the work in this field. To fill this gap, this …
Tkucheran
223
MemEvolve: Meta-Evolution of Agent Memory Systems
arXiv:2512.18746v1 Announce Type: new
Abstract: Self-evolving memory systems are unprecedentedly reshaping the evolutionary paradigm of large language model (LLM)-based agents. Prior work has predominantly relied on manually engineered memory architectures to store trajectories, distill experience,…
Abstract: Self-evolving memory systems are unprecedentedly reshaping the evolutionary paradigm of large language model (LLM)-based agents. Prior work has predominantly relied on manually engineered memory architectures to store trajectories, distill experience,…
Jasonbraun26
208
What-If Decision Support for Product Line Extension Using Conditional Deep Generative Models
arXiv:2511.11646v2 Announce Type: replace
Abstract: Product line extension is a strategically important managerial decision that requires anticipating how consumer segments and purchasing contexts may respond to hypothetical product designs that do not yet exist in the market. Such decisions are in…
Abstract: Product line extension is a strategically important managerial decision that requires anticipating how consumer segments and purchasing contexts may respond to hypothetical product designs that do not yet exist in the market. Such decisions are in…
Vw860813
118
Toward Human-Centered AI-Assisted Terminology Work
arXiv:2512.18859v1 Announce Type: new
Abstract: The rapid diffusion of generative artificial intelligence is transforming terminology work. While this technology promises gains in efficiency, its unstructured adoption risks weakening professional autonomy, amplifying bias, and eroding linguistic an…
Abstract: The rapid diffusion of generative artificial intelligence is transforming terminology work. While this technology promises gains in efficiency, its unstructured adoption risks weakening professional autonomy, amplifying bias, and eroding linguistic an…
Raselaman1973
110
OW-Rep: Open World Object Detection with Instance Representation Learning
arXiv:2409.16073v3 Announce Type: replace
Abstract: Open World Object Detection(OWOD) addresses realistic scenarios where unseen object classes emerge, enabling detectors trained on known classes to detect unknown objects and incrementally incorporate the knowledge they provide. While existing OWOD…
Abstract: Open World Object Detection(OWOD) addresses realistic scenarios where unseen object classes emerge, enabling detectors trained on known classes to detect unknown objects and incrementally incorporate the knowledge they provide. While existing OWOD…
Skipjayne
111
DIVER-1 : Deep Integration of Vast Electrophysiological Recordings at Scale
arXiv:2512.19097v1 Announce Type: new
Abstract: Electrophysiology signals such as EEG and iEEG are central to neuroscience, brain-computer interfaces, and clinical applications, yet existing foundation models remain limited in scale despite clear evidence that scaling improves performance. We intro…
Abstract: Electrophysiology signals such as EEG and iEEG are central to neuroscience, brain-computer interfaces, and clinical applications, yet existing foundation models remain limited in scale despite clear evidence that scaling improves performance. We intro…
J4janet
109
How I learned to stop worrying and love AI slop
Lately, everywhere I scroll, I keep seeing the same fish-eyed CCTV view: a grainy wide shot from the corner of a living room, a driveway at night, an empty grocery store. Then something impossible happens. JD Vance shows up at the doorstep in a crazy outfit. A car folds into itself like paper and dr…
Jasonbraun26