View-oriented Conversation Compiler for Agent Trace Analysis

arXiv:2603.29678 · cs.AI · Submitted 2026-03-31 · Read on arXiv

cs.AI

Submitted: 2026-03-31

Updated: 2026-08-30

Comments: Code: https://github.com/lllyasviel/VCC

Code: https://github.com/lllyasviel/VCC

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Trace — 34× in this paper · explained in 2 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Consistency — 6× in this paper · explained in 3 episodes
• View-oriented Conversation Compiler — 4× in this paper
• Embeddings — 3× in this paper · explained in 2 episodes
• Multi-Agent Framework — 3× in this paper · explained in 3 episodes
• AI Agents — 2× in this paper · explained in 2 episodes
• Abstraction — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Agentic System — 2× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 4 episodes
• Action Space — 1× in this paper · explained in 1 episode
• Agent Memory — 1× in this paper · explained in 1 episode
• Agentic Coding — 1× in this paper · explained in 1 episode
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Reasoning Traces — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes

Sources

• AgentTrace: A Structured Logging Framework for Agent System Observability
• AgentRx: Diagnosing AI Agent Failures from Execution Trajectories
• Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory
• TRAIL: Trace Reasoning and Agentic Issue Localization
• Context Length Alone Hurts LLM Performance Despite Perfect Retrieval
• Trajectory-Informed Memory Generation for Self-Improving Agent Systems
• Learning Hierarchical Procedural Memory for LLM Agents through Bayesian Selection and Contrastive Refinement
• AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents
• Does Prompt Formatting Have Any Impact on LLM Performance?
• Sample-Efficient Online Learning in LM Agents via Hindsight Trajectory Rewriting
• Memory in the Age of AI Agents
• AgentStepper: Interactive Debugging of Software Development Agents
• ACON: Optimizing Context Compression for Long-horizon LLM Agents
• The Complexity Trap: Simple Observation Masking Is as Efficient as LLM Summarization for Agent Context Management
• Lost in the Middle: How Language Models Use Long Contexts
• AgentBench: Evaluating LLMs as Agents
• Beyond Prompt Content: Enhancing LLM Performance via Content-Format Integrated Prompt Optimization
• DoVer: Intervention-Driven Auto Debugging for LLM Multi-Agent Systems
• A Survey of Context Engineering for Large Language Models
• MemGPT: Towards LLMs as Operating Systems

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