Lookahead-R: Budget-Aware Tool Retrieval via Execution-Centric Planning

arXiv:2609.35811 · cs.CL, cs.AI, cs.SE · Submitted 2026-09-20 · Read on arXiv

cs.CL, cs.AI, cs.SE

Submitted: 2026-09-20

Updated: 2026-09-20

Terminology

• World Model — 28× in this paper · explained in 7 episodes
• Large Language Model — 15× in this paper
• Trace — 10× in this paper · explained in 2 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Ablation — 6× in this paper · explained in 1 episode
• International Conference on Learning Representations — 6× in this paper
• Association for Computational Linguistics — 5× in this paper
• Monte Carlo Tree Search — 5× in this paper
• Pruning — 5× in this paper · explained in 4 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• Pass Rate — 4× in this paper
• Ablation Studies — 3× in this paper · explained in 1 episode
• Benchmarking — 3× in this paper · explained in 3 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Hallucination — 3× in this paper · explained in 3 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Affordance — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Core — 2× in this paper · explained in 2 episodes
• Epistemic Uncertainty — 2× in this paper · explained in 9 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Transactions on Machine Learning Research — 2× in this paper
• Adaptive Planning — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Dynamic Adaptation — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• In International Conference on Machine Learning — 1× in this paper
• Information Gain — 1× in this paper · explained in 2 episodes
• Introspection — 1× in this paper · explained in 2 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• Multi-Agent System — 1× in this paper · explained in 5 episodes
• Multi-modal Inputs — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Resource Constraints — 1× in this paper · explained in 3 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• WebSynthesis: World-Model-Guided MCTS for Efficient WebUI-Trajectory Synthesis
• The Llama 3 Herd of Models
• Where LLM Agents Fail and How They can Learn From Failures
• Budget-Aware Tool-Use Enables Effective Agent Scaling
• ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
• Enhancing Tool Retrieval with Iterative Feedback from Large Language Models
• Cost-Awareness in Tree-Search LLM Planning: A Systematic Study

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