Papers with Function calling empowers large language models
R2IF: Aligning Reasoning with Decisions via Composite Rewards for Interpretable LLM Function Calling (2026.acl-long)
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| Challenge: | Existing RL-based approaches to function calling are misaligned between reasoning processes and tool-call decisions. |
| Approach: | They propose a reasoning-aware RL framework for interpretable function calling . they integrate a composite reward integrating format/correctness constraints, CER, and SMV . |
| Outcome: | Experiments on BFCL/ACEBench show R2IF outperforms baselines by 34.62% with positive Average CoT Effectiveness. |