· ai
[Paper] Parallel Token Prediction for Language Models
We propose Parallel Token Prediction (PTP), a universal framework for parallel sequence generation in language models. PTP jointly predicts multiple dependent t...
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- · ai
[Paper] Variationally correct operator learning: Reduced basis neural operator with a posteriori error estimation
Minimizing PDE-residual losses is a common strategy to promote physical consistency in neural operators. However, standard formulations often lack variational c...
- · ai
[Paper] Scaling Laws for Economic Productivity: Experimental Evidence in LLM-Assisted Consulting, Data Analyst, and Management Tasks
This paper derives `Scaling Laws for Economic Impacts' -- empirical relationships between the training compute of Large Language Models (LLMs) and professional ...
- · ai
[Paper] Does the Data Processing Inequality Reflect Practice? On the Utility of Low-Level Tasks
The data processing inequality is an information-theoretic principle stating that the information content of a signal cannot be increased by processing the obse...
- · ai
[Paper] Learning to Solve PDEs on Neural Shape Representations
Solving partial differential equations (PDEs) on shapes underpins many shape analysis and engineering tasks; yet, prevailing PDE solvers operate on polygonal/tr...
- · ai
[Paper] AndroidLens: Long-latency Evaluation with Nested Sub-targets for Android GUI Agents
Graphical user interface (GUI) agents can substantially improve productivity by automating frequently executed long-latency tasks on mobile devices. However, ex...
- · ai
[Paper] Transcriptome-Conditioned Personalized De Novo Drug Generation for AML Using Metaheuristic Assembly and Target-Driven Filtering
Acute Myeloid Leukemia (AML) remains a clinical challenge due to its extreme molecular heterogeneity and high relapse rates. While precision medicine has introd...
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[Paper] Model Merging via Multi-Teacher Knowledge Distillation
Model merging has emerged as a lightweight alternative to joint multi-task learning (MTL), yet the generalization properties of merged models remain largely une...
- · ai
[Paper] Post-Processing Mask-Based Table Segmentation for Structural Coordinate Extraction
Structured data extraction from tables plays a crucial role in document image analysis for scanned documents and digital archives. Although many methods have be...
- · ai
[Paper] Surgical Scene Segmentation using a Spike-Driven Video Transformer with Real-Time Potential
Modern surgical systems increasingly rely on intelligent scene understanding to provide timely situational awareness for enhanced intra-operative safety. Within...
- · ai
[Paper] SMART SLM: Structured Memory and Reasoning Transformer, A Small Language Model for Accurate Document Assistance
The user of Engineering Manuals (EM) finds it difficult to read EM s because they are long, have a dense format which includes written documents, step by step p...
- · ai
[Paper] GriDiT: Factorized Grid-Based Diffusion for Efficient Long Image Sequence Generation
Modern deep learning methods typically treat image sequences as large tensors of sequentially stacked frames. However, is this straightforward representation id...