Can David Beat Goliath? On Multi-Hop Reasoning with Resource-Constrained Agents

arXiv:2601.21699 · cs.CL, cs.IR · Submitted 2026-01-29 · Read on arXiv

cs.CL, cs.IR

Submitted: 2026-01-29

Updated: 2026-09-26

Code: https://github.com/QwenLM/Qwen3

Terminology

• GRPO — 125× in this paper · explained in 6 episodes
• Benchmark — 26× in this paper · explained in 2 episodes
• Multi-hop Reasoning — 10× in this paper · explained in 3 episodes
• Reinforcement Learning — 9× in this paper · explained in 4 episodes
• World Classical Network — 9× in this paper
• Ablation — 7× in this paper · explained in 1 episode
• Accuracy — 6× in this paper · explained in 1 episode
• Exact Match — 5× in this paper
• Creation Ministries International — 4× in this paper
• Grounding — 3× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 3× in this paper · explained in 25 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Credit assignment — 2× in this paper · explained in 3 episodes
• F1 Score — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Action Space — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Agentic System — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• GRPO Objective — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Markov Decision Process (MDP) — 1× in this paper · explained in 10 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Resource Constraints — 1× in this paper · explained in 3 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Reward Shaping — 1× in this paper · explained in 2 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Workshop on Large Language Model — 1× in this paper

Sources

• The Compute Divide in Machine Learning: A Threat to Academic Contribution and Scrutiny?
• The Llama 3 Herd of Models
• Curriculum Guided Reinforcement Learning for Efficient Multi Hop Retrieval Augmented Generation
• Tree Search for LLM Agent Reinforcement Learning
• Qwen2.5 Technical Report
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Text Embeddings by Weakly-Supervised Contrastive Pre-training
• DAPO: An Open-Source LLM Reinforcement Learning System at Scale
• Agent models: Internalizing Chain-of-Action Generation into Reasoning models

Related papers

• Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
• Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
• Subliminal Steering: Stronger Encoding of Hidden Signals
• MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
• The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
• Untangling the Mechanisms of Misleading Context in Medical Question Answering