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cs.CL2026
Towards a Learnable Retriever for Textual Graph Question Answering
Kaifeng Jin, Yuchen Yan, Zhichen Zeng +4
Textual graph question answering (GraphQA) and graph-based retrieval-augmented generation (GraphRAG) have gained increasing attention as a way to ground large language models (LLMs…
cs.CL2026
Code as Agent Harness
Xuying Ning, Katherine Tieu, Dongqi Fu +39
Recent large language models (LLMs) have demonstrated strong capabilities in understanding and generating code, from competitive programming to repository-level software engineerin…