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cs.CL2026
UTILMEM: Benchmarking Evidence Utilization in Long-Term Conversational Memory
Peijun Qing, Fobo Shi, Soroush Vosoughi
Long-term memory is increasingly important for conversational agents, yet existing benchmarks primarily measure memory through pointwise factual recall: whether a system can recove…
cs.CL2026
Cluster-R1: Large Reasoning Models Are Instruction-following Clustering Agents
Peijun Qing, Puneet Mathur, Nedim Lipka +5
General-purpose embedding models excel at recognizing semantic similarities but fail to capture the characteristics of texts specified by user instructions. In contrast, instructio…