AdaTutoRank: Learning to Rerank Document Sets via Adaptive Tutoring Optimization for RAG and Deep Research
cs.CL
Submitted: 2026-09-26
Updated: 2026-09-29
Code: https://github.com/AdaTutoRank/AdaTutoRank
Project page: https://adatutorank.github.io
Terminology
Sources
- HealthBench: Evaluating Large Language Models Towards Improved Human Health
- OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs
- Rank4Gen: RAG-Preference-Aligned Document Set Selection and Ranking
- Can Multimodal Large Language Models Understand OCT?
- Retrieval-Augmented Generation for Large Language Models: A Survey
- Reinforcement Learning via Self-Distillation
- Beyond Relevance-Centric Retrieval: Rubric-Oriented Document Set Selection and Ranking
- Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
- KnowHal: A Knowledge-Driven Benchmark for Comprehensive Multimodal Hallucination Evaluation
- From Proprietary to Open-Source: Bridging the Distribution Gap via Multi-Agent Protocol Distillation in Agentic Search
- Training Documents Reranker with Search Rubrics for Deep Research Agent
- Can Visual Input Be Compressed? A Visual Token Compression Benchmark for Large Multimodal Models
- RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models
- RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!
- DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Self-Distillation Enables Continual Learning
- Deep Research: A Systematic Survey
- A Comprehensive Survey of Deep Research: Systems, Methodologies, and Applications
- ReAct: Synergizing Reasoning and Acting in Language Models
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