1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CL2026
ArgBench: Benchmarking LLMs on Computational Argumentation Tasks
Yamen Ajjour, Carlotta Quensel, Nedim Lipka +1
Argumentation skills are an essential toolkit for large language models (LLMs). These skills are crucial in various use cases, including self-reflection, debating collaboratively f…
cs.IR2026★ 1 cited
SmartChunk Retrieval: Query-Aware Chunk Compression with Planning for Efficient Document RAG
Xuechen Zhang, Koustava Goswami, Samet Oymak +2
Retrieval-augmented generation (RAG) has strong potential for producing accurate and factual outputs by combining language models (LMs) with evidence retrieved from large text corp…