Papers with retrieval strategies
EdTec-QBuilder: A Semantic Retrieval Tool for Assembling Vocational Training Exams in German Language (2024.naacl-demo)
Copied to clipboard
| Challenge: | Existing methods to gather test items from validated item databases are under-researched, but there is little research on assembling exam items from a database of valid items. |
| Approach: | They propose to use semantic search to assist vocational educators in assembling exam forms by using eight retrieval strategies and 25 popular sentence similarity models. |
| Outcome: | The proposed tool is based on eight retrieval strategies and 25 popular pre-trained sentence similarity models. |
An Efficient Context-Dependent Memory Framework for LLM-Centric Agents (2025.naacl-industry)
Copied to clipboard
| Challenge: | a recent study has demonstrated that context-dependent memory encoding can help to retrieve key memory cues essential for problem-solving. |
| Approach: | They propose an efficient architecture miming human memory processes through multistage encoding, context-aware storage, and retrieval strategies for LLM-centric agents. |
| Outcome: | The proposed architecture surpasses state-of-the-art online LLM-centric approaches on two interactive decision-making benchmarks in the navigation and manipulation domain. |
DRUM: Learning Demonstration Retriever for Large MUlti-modal Models (2025.acl-srw)
Copied to clipboard
| Challenge: | Recent studies have shown that large language models (LLMs) have impressive capabilities in dealing with new tasks with the help of in-context learning (ICL). |
| Approach: | They propose to concate the image and text embeddings to enhance the retrieval performance of a visual-language task and to calculate a list-wise ranking loss for training the embeddable model. |
| Outcome: | The proposed framework fine-tunes the CLIP embedding model to better meet the needs of the large vision-language models. |
Retrieval Augmented Instruction Tuning for Open NER with Large Language Models (2025.coling-main)
Copied to clipboard
| Challenge: | Existing studies have focused on integrating large language models (LLMs) with information extraction (IE) however, the best approach to incorporate information with LLMs for IE remains an open question. |
| Approach: | They propose to use a Chinese IT dataset to perform RA-IT for IE . they use semantically similar examples from the training dataset as the context . |
| Outcome: | The proposed approach is evaluated in English and Chinese scenarios. |
Enhancing Retrieval-Augmented Generation: A Study of Best Practices (2025.coling-main)
Copied to clipboard
| Challenge: | Retrieval-augmented generation systems have shown remarkable advancements by integrating retrieval mechanisms into language models, enhancing their ability to produce more accurate and contextually relevant responses. |
| Approach: | They propose to integrate query expansion, various novel retrieval strategies, and a Contrastive In-Context Learning RAG to improve response quality. |
| Outcome: | The proposed RAGs incorporate query expansion, various novel retrieval strategies, and a novel Contrastive In-Context Learning RAG. |
AIRCoder: Adaptive Integration of Multi-dimensional Retrieval for Repository-level Code Completion (2026.acl-long)
Copied to clipboard
| Challenge: | Existing methods for retrieving code from large codebases use textual similarity or dependency existence, resulting in inconsistent performance. |
| Approach: | They propose a retrieval framework that integrates eight complementary metrics across three dimensions: textual similarity, dependency existence, and structural hierarchy. |
| Outcome: | Experiments on CrossCodeEval and RepoEval show that AIRCoder improves accuracy and performance by 10.2 over baseline methods. |