Calibration is the Bottleneck: An Action-Class Diagnostic of Multi-Turn Tool-Calling

arXiv:2609.00949 · cs.CL, cs.AI · Submitted 2026-09-01 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-09-01

Updated: 2026-09-24

Code: https://github.com/fbj2333/tool-calling-calibration

Terminology

• Calibration — 30× in this paper · explained in 7 episodes
• Benchmark — 29× in this paper · explained in 2 episodes
• Accuracy — 14× in this paper · explained in 1 episode
• Ablation — 13× in this paper · explained in 1 episode
• Abstention — 8× in this paper · explained in 1 episode
• Berkeley Function Calling Leaderboard — 4× in this paper
• Action Space — 3× in this paper · explained in 1 episode
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• State-Reconciliation Intervention — 3× in this paper
• Aggregation — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Call-Reconciliation Intervention — 2× in this paper
• Failure Modes — 2× in this paper · explained in 3 episodes
• Gold Action Recall — 2× in this paper
• Adam — 1× in this paper · explained in 2 episodes
• Agentic Evaluation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• GRPO — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Halt Detector — 1× in this paper
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 1× in this paper
• International Conference on Machine Learning — 1× in this paper
• LLM judge — 1× in this paper · explained in 2 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• AgentRx: Diagnosing AI Agent Failures from Execution Trajectories
• $\tau^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment
• ToolExpander: Extending the Frontiers of Tool-Using Reinforcement Learning to Weak LLMs
• Beyond Task Completion: Revealing Corrupt Success in LLM Agents through Procedure-Aware Evaluation
• Calibrate-Then-Act: Cost-Aware Exploration in LLM Agents
• The Llama 3 Herd of Models
• Auditing Automated Evaluation, Error Propagation, and Runtime Mitigation in Tool-Using Language Agents
• ToolCritic: Detecting and Correcting Tool-Use Errors in Dialogue Systems
• Capable but Unreliable: Canonical Path Deviation as a Causal Mechanism of Agent Failure in Long-Horizon Tasks
• Improve Mathematical Reasoning in Language Models by Automated Process Supervision
• Failure Makes the Agent Stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions
• Why Reasoning Fails to Plan: A Planning-Centric Analysis of Long-Horizon Decision Making in LLM Agents
• Qwen3 Technical Report
• $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains
• Nemotron-Research-Tool-N1: Exploring Tool-Using Language Models with Reinforced Reasoning
• RC-GRPO: Reward-Conditioned Group Relative Policy Optimization for Multi-Turn Tool Calling Agents
• Where LLM Agents Fail and How They can Learn From Failures

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