8 papers
StateTape: Action-Conditioned Evidence Lifecycle Modeling for Long-Horizon Coding Agents
Ziyang Yu, Liang Zhao, Bowen Zhu +1
Despite the recent success of coding agents built on large language models, it remains challenging to run them over long horizons, since every observation is appended to the contex…
MEMONDEMAND: A Memory Management System for Large-Scale Enterprise Data
Xinyuan Song, Bowen Zhu, Hasibul Haque +1
Enterprise repositories are large, heteroge- neous, and continuously updated, making re- trieval difficult when efficient access, source- faithful evidence, and cross-query adaptat…
MegaMem: A Retrieval Solution for Ultra-Large Context Windows
Xinyuan Song, Bowen Zhu, Hasibul Haque +1
Modern language models and agents increasingly require persistent memory for complete codebases, long interaction histories, and heterogeneous enterprise records. The key challenge…
In-Context Optimization for Retrieval-Augmented Generation: A Gradient-Descent Perspective
Mingchen Li, Jiatan Huang, Chuxu Zhang +2
In-context learning has recently been linked to implicit gradient descent in linear self-attention models, suggesting that context can induce a forward-pass update. Retrieval-augme…
LARGER: Lexically Anchored Repository Graph Exploration and Retrieval
Yuntong Hu, Tongli Su, Liang Zhao +2
Repository-level coding agents must first localize the files and symbols relevant to a task; failures at this stage can cascade across downstream objectives ranging from patch gene…
Decompose, Look, and Reason: Reinforced Latent Reasoning for VLMs
Mengdan Zhu, Senhao Cheng, Liang Zhao
Vision-Language Models often struggle with complex visual reasoning due to the visual information loss in textual CoT. Existing methods either add the cost of tool calls or rely on…
RAG without Forgetting: Continual Query-Infused Key Memory
Yuntong Hu, Sha Li, Naren Ramakrishnan +1
Retrieval-augmented generation (RAG) systems commonly improve robustness via query-time adaptations such as query expansion and iterative retrieval. While effective, these approach…
Multimodal Representation Learning Conditioned on Semantic Relations
Yang Qiao, Yuntong Hu, Bowen Zhu +2
Multimodal representation learning has been largely driven by contrastive models such as CLIP, which learn a shared embedding space by aligning paired image-text samples. While eff…