GPUs, training clusters, MLOps, and deployment
UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...
1 is a fluke. 2 is a coincidence. 3 is a pattern. Lately I’ve been noticing something. The problems I’m solving are getting more complex…...
1 is a fluke. 2 is a coincidence. 3 is a pattern. Lately I’ve been noticing something. The problems I’m solving are getting more complex…...
![[2602.20217] KnapSpec: Self-Speculative Decoding via Adaptive Layer Selection as a Knapsack Problem](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper introduces KnapSpec, a framework for self-speculative decoding that optimizes layer selection in LLMs as a knapsack problem, en...
This paper proposes the 'Right to History,' a principle ensuring individuals have a verifiable record of AI agent actions on personal har...
This paper presents ESM, a novel framework for merging multiple task-specific models into a single multi-task model, addressing inter-tas...
This article discusses the concept of 'golden layers' in large language models (LLMs) and presents a novel method, Layer Gradient Analysi...
This paper analyzes the effectiveness of latency hiding and parallelism techniques in an MLIR-based AI kernel compiler, focusing on vecto...
The paper presents OptimusVLA, a dual-memory framework for robotic manipulation that enhances efficiency and robustness in action generat...
The OpenPort Protocol introduces a governance-first approach for AI agents, ensuring secure access to application tools while addressing ...
The paper presents MoBiQuant, a novel quantization framework for elastic large language models (LLMs) that adapts weight precision based ...
This article explores the ownership rules surrounding AI-generated outputs, examining how they are linked to their creators and the impli...
This paper presents JurisMMA, a novel framework for Legal Judgment Prediction (LJP) that utilizes multimodal data to enhance the accuracy...
The paper explores how Large Language Models (LLMs) can achieve superintelligence through the Diligent Learner framework, emphasizing the...
The paper introduces AgentOS, a conceptual framework that transitions Large Language Models from static inference engines to dynamic cogn...
The paper presents CHESS, a novel KV-cache management system designed for long-context LLM inference, enhancing efficiency and throughput...
This paper explores the use of reinforcement learning from AI feedback (RLAIF) to balance multiple objectives in urban traffic control, a...
The paper introduces Counterfactual Simulation Training (CST), a method designed to enhance Chain-of-Thought (CoT) faithfulness in large ...
The paper introduces ICON, a novel framework designed to defend Large Language Model (LLM) agents against Indirect Prompt Injection (IPI)...
The Recursive Belief Vision Language Model (RB-VLA) addresses limitations in current vision-language-action models by introducing a belie...
This paper explores the challenges of ensuring safety in AI systems using untrusted monitoring. It develops a taxonomy of collusion strat...
The CausalReasoningBenchmark introduces a new framework for evaluating automated causal inference, distinguishing between identification ...
The paper presents ActionEngine, a novel framework that enhances GUI agents by transitioning from reactive execution to programmatic plan...
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