·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws10h◆Bridging AI and Clinical Reasoning: Abductive Explanations for Alignment on Critical Symptoms10h◆CHASD: Language Increment-Calibrated Contrastive Decoding against Hallucination in LVLMs10h◆Prudent-Banker: No Extra Fees for Baseline Safety in Adversarial Bandits With and Without Delays10h◆InfiGFusion: Graph-on-Logits Distillation via Efficient Gromov-Wasserstein for Model Fusion10h◆Representational Alignment with Chemical Induced Fit for Molecular Relational Learning10h◆One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents10h◆RAG4Outcome: A Retrieval-Augmented Multimodal Framework for Prognostic Prediction in Chronic Osteomyelitis10h◆Uncovering the Latent Potential of Deep Intermediate Representations10h◆OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents10h◆Beyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum10h◆Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models10h◆FATHOMS-RAG: A Framework for the Assessment of Thinking and Observation in Multimodal Systems that use Retrieval Augmented Generation10h◆SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-Based Humanoid Control10h◆Detecting Drunk Driving Using Off-the-Shelf Smartwatches10h◆Decision-Aware Quadratic ReLU Replacement for HE-Friendly Inference10h◆MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks10h◆NeuroNL2LTL: A Neurosymbolic Framework for Natural Language Translation of Linear Temporal Logic10h◆Agentic Proving for Program Verification10h◆Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents10h◆LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws10h◆Bridging AI and Clinical Reasoning: Abductive Explanations for Alignment on Critical Symptoms10h◆CHASD: Language Increment-Calibrated Contrastive Decoding against Hallucination in LVLMs10h◆Prudent-Banker: No Extra Fees for Baseline Safety in Adversarial Bandits With and Without Delays10h◆InfiGFusion: Graph-on-Logits Distillation via Efficient Gromov-Wasserstein for Model Fusion10h◆Representational Alignment with Chemical Induced Fit for Molecular Relational Learning10h◆One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents10h◆RAG4Outcome: A Retrieval-Augmented Multimodal Framework for Prognostic Prediction in Chronic Osteomyelitis10h◆Uncovering the Latent Potential of Deep Intermediate Representations10h◆OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents10h◆Beyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum10h◆Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models10h◆FATHOMS-RAG: A Framework for the Assessment of Thinking and Observation in Multimodal Systems that use Retrieval Augmented Generation10h◆SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-Based Humanoid Control10h◆Detecting Drunk Driving Using Off-the-Shelf Smartwatches10h◆Decision-Aware Quadratic ReLU Replacement for HE-Friendly Inference10h◆MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks10h◆NeuroNL2LTL: A Neurosymbolic Framework for Natural Language Translation of Linear Temporal Logic10h◆Agentic Proving for Program Verification10h◆Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents10h◆
News/Token Economics for LLM Agents: A Dual-View Study from Computing and Economics
arxiv
PublishedMay 13, 2026 at 4:00 AM

Token Economics for LLM Agents: A Dual-View Study from Computing and Economics

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2605.09104v1 Announce Type: new Abstract: As LLM agents evolve, tokens have emerged as the core economic primitives of Agentic AI. However, their exponential consumption introduces severe computational, collaborative, and security bottlenecks. Current surveys remain fragmented across system op

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivLLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws10harxivBridging AI and Clinical Reasoning: Abductive Explanations for Alignment on Critical Symptoms10harxivCHASD: Language Increment-Calibrated Contrastive Decoding against Hallucination in LVLMs10harxivPrudent-Banker: No Extra Fees for Baseline Safety in Adversarial Bandits With and Without Delays10h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews