Effective Dense Retrieval using Only In-Context Examples

arXiv:2609.38099 · cs.IR, cs.CL · Submitted 2026-09-29 · Read on arXiv

cs.IR, cs.CL

Submitted: 2026-09-29

Updated: 2026-09-29

Code: https://github.com/nourj98/RICE

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

Terminology

• Accuracy — 7× in this paper · explained in 1 episode
• Embeddings — 6× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes

Sources

• LLM2Vec-Gen: Generative Embeddings from Large Language Models
• A Systematic Study of Pseudo-Relevance Feedback with LLMs
• Qwen3 Technical Report
• Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

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