Theme of inquiry
How can retrieval systems better handle complex queries and conflicts?
A question within its area, explored through 7 lines of inquiry below — each a family of specific questions the research asks.
18 specific questions
- Can question quality be trained separately from the decision to ask?
- Can Q-priming further strengthen clarifying question behavior beyond social meta-learning alone?
- Why do question types determine retrieval and decomposition strategy in QA?
- Can attribute-specific preference optimization improve question quality in information-seeking?
- How do comparison and debate questions differ in their aspect retrieval needs?
- Can the eight-dimension rubric predict which question types need decomposition?
- How does the Question Under Discussion shape what content projects?
48 specific questions
- Can knowledge graph structure be exploited for efficient multi-hop retrieval?
- How do community-based summaries differ from retrieval-based traversal in knowledge graph RAG?
- How can knowledge graphs improve over pure embedding retrieval?
- When should you use knowledge graphs instead of semantic vector retrieval systems?
- How do graph databases address the relational query failures that LLMs encounter?
- Can graph-based retrieval with knowledge graphs scale to multi-hop reasoning?
- Can knowledge graph structure help embeddings represent more combinations?
56 specific questions
- Can adaptive retrieval triggered by model uncertainty improve RAG reliability?
- How should retrieval systems decide when to fetch new information?
- Should retrieval be triggered always or only for difficult questions?
- How does uncertainty-gated retrieval compare to continuous retrieval efficiency?
- Should retrieval be triggered by model uncertainty or fixed intervals?
- Are uncertainty estimation and external feature signals complementary for retrieval?
- How much does retrieval budget improve when triggered by dual signals instead of fixed intervals?
60 specific questions
- Why do embedding-based retrieval systems fail on vocabulary mismatch?
- Why do semantic similarity and task relevance diverge in vector search results?
- How do vector embeddings fail to capture task-relevant document relationships?
- Can vector embeddings measure task relevance instead of semantic similarity?
- Can embedding-based retrieval alone solve the causal relevance problem?
- What makes vector embeddings fail on single-hop semantic relevance queries?
- What mathematical limits constrain embedding-based retrieval systems?
32 specific questions
- What is the optimal balance between search rounds and reasoning depth per round?
- Does unrestricted reasoning per search step degrade iterative quality over time?
- Can adaptive per-step decisions outperform uniform retrieval policies across different reasoning tasks?
- How should iterative research tasks limit context per reasoning turn?
- Do single-step retrieval systems with sophisticated synthesis qualify as deep research?
- How does search budget affect answer quality at test time?
- Why do per-turn thinking budgets matter alongside iterative retrieval depth?
50 specific questions
- Can provenance tracking prevent synthetic content from polluting the corpus?
- How do entailment checks prevent synthetic data from degrading retrieval corpora?
- Can marking AI provenance solve the grounding problem for generated text?
- How do retrieval failures enable generation of fabricated scholarly constructs?
- Can we verify fabricated text without redesigning the generation process?
- Can citation practices work when AI cannot produce traceable sources?
- Can verification mechanisms prevent AI agents from inventing false citations?
32 specific questions
- How do hierarchical query planning architectures improve multi-hop retrieval?
- How should retrieval systems handle multi-hop reasoning and iterative information needs?
- How does query planning as a separate step improve multi-hop retrieval coherence?
- How do parallel and sequential retrieval strategies compare in compute efficiency?
- Does parallel retrieval outperform sequential search chains at test time?
- How does query decomposition reduce retrieval costs at inference?
- How do hierarchical research architectures handle multi-hop queries better?