## DeepResearch-Slice: A New Approach to Data Analysis DeepResearch-Slice is a new framework designed to improve the effectiveness of research agents in utilizing retrieved information. The system focuses on reducing the gap between data retrieval and its actual application, a common problem in noisy environments. ## How it Works Unlike implicit attention mechanisms, DeepResearch-Slice predicts precise span indices to perform a deterministic hard filter of the data before reasoning. This neuro-symbolic approach allows for the isolation of the most relevant information, improving the robustness of the system. ## Results and Benefits Evaluations across six benchmarks have demonstrated significant robustness gains. In particular, applying DeepResearch-Slice to frozen backbones led to a 73% relative improvement, mitigating noise without requiring parameter updates to the reasoning model. These results highlight the importance of explicit grounding mechanisms in open-ended research. In summary, DeepResearch-Slice represents a step forward towards more efficient and reliable research agents, capable of making the most of the information available to them.