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ArXiv cs.AI 📄 Paper 1d ago
Aligned Vector Quantization for Edge-Cloud Collabrative Vision-Language Models
arXiv:2411.05961v2 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) are central to Visual Question Answering (VQA) systems and are typically
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ArXiv cs.AI 📄 Paper 1d ago
Retrieval Augmented Time Series Forecasting
arXiv:2411.08249v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) is a central component of modern LLM systems, particularly in sce
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ArXiv cs.AI 📄 Paper 1d ago
VarDrop: Enhancing Training Efficiency by Reducing Variate Redundancy in Periodic Time Series Forecasting
arXiv:2501.14183v3 Announce Type: replace-cross Abstract: Variate tokenization, which independently embeds each variate as separate tokens, has achieved remarka
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ArXiv cs.AI 📄 Paper 1d ago
ENTER: Event Based Interpretable Reasoning for VideoQA
arXiv:2501.14194v2 Announce Type: replace-cross Abstract: In this paper, we present ENTER, an interpretable Video Question Answering (VideoQA) system based on e
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ArXiv cs.AI 📄 Paper 1d ago
An Innovative Next Activity Prediction Using Process Entropy and Dynamic Attribute-Wise-Transformer in Predictive Business Process Monitoring
arXiv:2502.10573v2 Announce Type: replace-cross Abstract: Next activity prediction in predictive business process monitoring is crucial for operational efficien
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ArXiv cs.AI 📄 Paper 1d ago
LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification
arXiv:2502.17421v3 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) can now process extremely long contexts, efficient inference over thes
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ArXiv cs.AI 📄 Paper 1d ago
Hedging and Non-Affirmation: Quantifying LLM Alignment on Questions of Human Rights
arXiv:2502.19463v2 Announce Type: replace-cross Abstract: Hedging and non-affirmation are behaviors exhibited by large language models (LLMs) that limit the cle
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ArXiv cs.AI 📄 Paper 1d ago
NativQA Framework: Enabling LLMs and VLMs with Native, Local, and Everyday Knowledge
arXiv:2504.05995v3 Announce Type: replace-cross Abstract: The rapid progress of large language models (LLMs) raises concerns about cultural bias, fairness, and
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ArXiv cs.AI 📄 Paper 1d ago
Phonetic Perturbations Reveal Tokenizer-Rooted Safety Gaps in LLMs
arXiv:2505.14226v5 Announce Type: replace-cross Abstract: Safety-aligned LLMs remain vulnerable to digital phenomena like textese that introduce non-canonical p
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ArXiv cs.AI 📄 Paper 1d ago
The Polar Express: Optimal Matrix Sign Methods and Their Application to the Muon Algorithm
arXiv:2505.16932v4 Announce Type: replace-cross Abstract: Computing the polar decomposition and the related matrix sign function has been a well-studied problem
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ArXiv cs.AI 📄 Paper 1d ago
Synthesis of discrete-continuous quantum circuits with multimodal diffusion models
arXiv:2506.01666v3 Announce Type: replace-cross Abstract: Efficiently compiling quantum operations remains a major bottleneck in scaling quantum computing. Toda
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ArXiv cs.AI 📄 Paper 1d ago
HeartcareGPT: A Unified Multimodal ECG Suite for Dual Signal-Image Modeling and Understanding
arXiv:2506.05831v4 Announce Type: replace-cross Abstract: Although electrocardiograms (ECG) play a dominant role in cardiovascular diagnosis and treatment, thei
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ArXiv cs.AI 📄 Paper 1d ago
BulletGen: Improving 4D Reconstruction with Bullet-Time Generation
arXiv:2506.18601v2 Announce Type: replace-cross Abstract: Transforming casually captured, monocular videos into fully immersive dynamic experiences is a highly
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ArXiv cs.AI 📄 Paper 1d ago
A Survey of Continual Reinforcement Learning
arXiv:2506.21872v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) is an important machine learning paradigm for solving sequential decision-
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ArXiv cs.AI 📄 Paper 1d ago
Enhancing Hallucination Detection via Future Context
arXiv:2507.20546v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are widely used to generate plausible text on online platforms, without r
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ArXiv cs.AI 📄 Paper 1d ago
Aleatoric Uncertainty Medical Image Segmentation Estimation via Flow Matching
arXiv:2507.22418v3 Announce Type: replace-cross Abstract: Quantifying aleatoric uncertainty in medical image segmentation is critical since it is a reflection o
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ArXiv cs.AI 📄 Paper 1d ago
Pursuit of biomarkers of brain diseases: Beyond cohort comparisons
arXiv:2509.10547v2 Announce Type: replace-cross Abstract: Despite the diversity and volume of brain data acquired and advanced AI-based algorithms to analyze th
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ArXiv cs.AI 📄 Paper 1d ago
LifeAlign: Lifelong Alignment for Large Language Models with Memory-Augmented Focalized Preference Optimization
arXiv:2509.17183v2 Announce Type: replace-cross Abstract: Alignment plays a crucial role in Large Language Models (LLMs) in aligning with human preferences on a
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ArXiv cs.AI 📄 Paper 1d ago
A State-Update Prompting Strategy for Efficient and Robust Multi-turn Dialogue
arXiv:2509.17766v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) struggle with information forgetting and inefficiency in long-horizon, mu
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ArXiv cs.AI 📄 Paper 1d ago
Chiplet-Based RISC-V SoC with Modular AI Acceleration
arXiv:2509.18355v5 Announce Type: replace-cross Abstract: Achieving high performance, energy efficiency, and cost-effectiveness while maintaining architectural
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ArXiv cs.AI 📄 Paper 1d ago
StateX: Enhancing RNN Recall via Post-training State Expansion
arXiv:2509.22630v2 Announce Type: replace-cross Abstract: Recurrent neural networks (RNNs), such as linear attention and state-space models, have gained popular
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ArXiv cs.AI 📄 Paper 1d ago
Dissecting Transformers: A CLEAR Perspective towards Green AI
arXiv:2510.02810v2 Announce Type: replace-cross Abstract: The rapid adoption of Large Language Models (LLMs) has raised significant environmental concerns. Unli
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ArXiv cs.AI 📄 Paper 1d ago
Reveal-to-Revise: Explainable Bias-Aware Generative Modeling with Multimodal Attention
arXiv:2510.12957v3 Announce Type: replace-cross Abstract: We present an explainable, bias-aware generative framework that unifies cross-modal attention fusion,
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ArXiv cs.AI 📄 Paper 1d ago
Unlocking the Potential of Diffusion Language Models through Template Infilling
arXiv:2510.13870v2 Announce Type: replace-cross Abstract: Diffusion Language Models (DLMs) have emerged as a promising alternative to Autoregressive Language Mo
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