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cs.IR2026
RAG over Thinking Traces Can Improve Reasoning Tasks
Negar Arabzadeh, Wenjie Ma, Sewon Min +1
Retrieval-augmented generation (RAG) has proven effective for knowledge-intensive tasks, but is widely believed to offer limited benefit for reasoning-intensive problems such as ma…
cs.IR2026
PIXELRAG: Web Screenshots Beat Text for Retrieval-Augmented Generation
Yichuan Wang, Zhifei Li, Zirui Wang +5
Augmenting large language models (LLMs) with retrieved web text has become a dominant paradigm, yet the web is not natively textual: existing systems depend on complex parsing pipe…