GPUs, training clusters, MLOps, and deployment
What it does: You give it any input — a blog URL, a YouTube video, raw text, or just a topic — and it generates optimized posts for 9 pla...
there's this network that launched recently routing crypto mining hardware toward AI training workloads. miners seem happy with the econo...
![[2604.01989] Attention at Rest Stays at Rest: Breaking Visual Inertia for Cognitive Hallucination Mitigation](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2604.01989: Attention at Rest Stays at Rest: Breaking Visual Inertia for Cognitive Hallucination Mitigation
The paper introduces KVComm, a novel framework for efficient communication between Large Language Models (LLMs) using selective KV pair s...
This paper presents a novel method, Elsa, for achieving extreme sparsity in large language models (LLMs) without sacrificing accuracy, ad...
The article introduces ToolSelf, a novel framework for enhancing agentic systems using Large Language Models (LLMs) by enabling runtime s...
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This article explores lightweight error mitigation strategies for post-training N:M activation sparsity in large language models (LLMs), ...
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This paper presents a novel approach to privacy-aware Bayesian networks using credal networks, addressing the trade-off between privacy a...
This article introduces Conflict-Aware Fusion, a framework designed to address Logic Inertia in large language models (LLMs) by integrati...
This article presents Exploratory Iteration (ExIt), a novel approach in reinforcement learning that enhances self-improvement in agents b...
This article presents a novel approach to local Stochastic Gradient Descent (SGD) for deep learning on heterogeneous systems, demonstrati...
The paper discusses AI agents as stochastic dynamical systems, emphasizing their ability to learn and reason through transductive inferen...
The paper presents Modular Delta Merging with Orthogonal Constraints (MDM-OC), a framework for scalable and reversible model composition ...
This article presents a novel approach to adversarial attacks on large language models (LLMs) by incorporating sampling strategies, signi...
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This article presents a novel method, Physics-Based Flow Matching (PBFM), which integrates physical constraints into generative modeling,...
The paper presents E-BATS, a novel framework for efficient backpropagation-free test-time adaptation (TTA) tailored for speech foundation...
This paper presents a novel optimization framework for large language models (LLMs) based on generalized Gaussian distributions, enhancin...
The paper introduces V-Droid, a mobile GUI task automation agent that utilizes a verifier-driven approach, enhancing decision-making and ...
The article presents CodePDE, an innovative framework leveraging large language models (LLMs) for generating solvers for partial differen...
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