人工智能
83 篇 · 资讯流Conflicted Records: Typed Adversarial Contracts for Auditable LLM Output Quality Enforcement
LLM-generated records increasingly populate production information systems where they are treated as data assets subject
原文 ↗UniWALM: Unified World Action Language Model for Embodied Robot Control
Motivated by the human ability to integrate experience across language, perception, and action, we introduce UniWALM, a
原文 ↗BitMTP: When Multi-Token Prediction Meets Low-Bit Large Language Models
For efficient deployment of large language models (LLMs), methods of ultra-low-bit backbones reduce weight storage, memo
原文 ↗MAS-Guard: Unified Guardrails from Individual Agents to Multi-Agent LLM Systems
Agentic AI extends large language models (LLMs) from generating responses to planning and executing complex workflows, s
原文 ↗Local Work, Global Progress: A Convergence Theory of AI Agent Collaboration
Teams of large language model (LLM) agents are increasingly applied to complex tasks, but their collaboration protocols
原文 ↗Temporal Evidence-Parameter Co-Alignment for LLM Reasoning over Temporal Knowledge Graphs
Large Language Models (LLMs) often struggle with temporally grounded reasoning because their static parametric memory is
原文 ↗CovNav: Conformal Prediction-Guided Adaptive Inference for Object Goal Navigation
In object goal navigation (ObjectNav), an embodied agent must find a target object (e.g., "find a bed") in a previously
原文 ↗ATEST: Adaptive Resource-Aware Test-Time Scaling for LLM Inference
Test-time scaling (TTS) improves large language model (LLM) reasoning by sampling multiple answers, but fixed sampling b
原文 ↗Designing for Imperfect Prompts: A Simulation-Based Evaluation of an LLM-Based Enterprise Data Assistant Using Knowledge Graphs
Enterprise data assistants using large language models (LLMs) promise democratized data access in organizations. Yet in
原文 ↗Unifying Embodied Foundation Models via a Model-to-Policy Formulation
Vision-language-action (VLA) models and world-action models (WAMs) have emerged as promising approaches to robot learnin
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