Configurable Semantic Chunking for Biomedical Information Extraction in Retrieval-Augmented Generation

arXiv:2608.31139 · cs.CL, cs.IR · Submitted 2026-08-31 · Read on arXiv

cs.CL, cs.IR

Submitted: 2026-08-31

Updated: 2026-08-31

Comments: 9 pages, 7 tables

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

Terminology

• Ablation — 10× in this paper · explained in 1 episode
• Benchmark — 9× in this paper · explained in 2 episodes
• RAG — 9× in this paper · explained in 3 episodes
• alpha — 7× in this paper · explained in 1 episode
• Cosine Similarity — 5× in this paper · explained in 3 episodes
• Embeddings — 5× in this paper · explained in 2 episodes
• Ablation Studies — 3× in this paper · explained in 1 episode
• Adaptation — 3× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• In International Conference on Learning Representations — 2× in this paper
• In-Context Learning — 2× in this paper · explained in 4 episodes
• Interpretability — 2× in this paper · explained in 15 episodes
• Semantic Similarity — 2× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Empirical Methods in Natural Language Processing — 1× in this paper
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Quantization — 1× in this paper · explained in 12 episodes

Sources

• Retrieval-Augmented Generation for Large Language Models: A Survey
• Late Chunking: Contextual Chunk Embeddings Using Long-Context Embedding Models
• Scalable and Domain-General Abstractive Proposition Segmentation
• Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

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