Super Research: Answering Highly Complex Questions with Large Language Models through Super Deep and Super Wide Research
While Large Language Models (LLMs) have demonstrated proficiency in Deep Research or Wide Search, their capacity to solve highly complex questions-those requiring long-horizon planning, massive evidence gathering, and synthesis across heterogeneous sources-remains largely unexplored. We introduce Super Research, a task for complex autonomous research tasks that integrates (i) structured decomposition into a research plan, (ii) super wide retrieval for diverse perspectives, and (iii) super deep investigation to resolve uncertainties through iterative queries. To evaluate this capability, we curated a benchmark of 300 expert-written questions across diverse domains, each requiring up to 100...
| Authors | Yubo Dong, Nianhao You, Yuxuan Hou et al. |
|---|---|
| Primary category | cs.CL |
| Published | 28 February 2026 |
| Last updated at source | 3 March 2026 |
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