Papers with hierarchical strategy

3 papers
ZoomR: Memory Efficient Reasoning through Multi-Granularity Key Value Retrieval (2026.acl-long)

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Challenge: Large language models generate long chain of thoughts but memory footprint grows with output length . prior work on KV cache optimization focused on compressing long input context .
Approach: They propose a new approach that compresses verbose reasoning thoughts into summaries . they use a dynamic KV cache selection policy that leverages these summary keys .
Outcome: The proposed approach reduces memory usage while avoiding full-cache attention at each step.
Chinese-Portuguese Machine Translation: A Study on Building Parallel Corpora from Comparable Texts (L18-1)

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Challenge: Chinese and Portuguese are very populous languages, but there is not much parallel corpora in the Chinese-Portuguese language pair.
Approach: They propose to curate Chinese-Portuguese parallel corpora and evaluate their quality . they extract bilingual data from government websites and use Phrased-Based Machine Translation (PBMT) and Neural Machine Translation models to build large corpus.
Outcome: The proposed method can be used as a benchmark for future Chinese-Portuguese MT systems.
Mobile-R1: Towards Interactive Capability for VLM-Based Mobile Agent via Systematic Training (2026.acl-long)

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Challenge: Existing approaches to training agents for visual-language models trap them in local optima, hindering exploration and error correction with the environment.
Approach: They propose a hierarchical training recipe that bridges atomic action execution and strategic task completion.
Outcome: The proposed training recipe bridges atomic action execution and strategic task completion.

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