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cs.AI2026
The Retriever Should Remember: Experience-Amortized Reranking for Long-Term Agent Memory
Qi Feng, Chris Ding, Jicong Fan
Long-term language-model agents accumulate memories across interactions, but their retrievers typically do not accumulate retrieval experience. Semantic retrieval is efficient, but…
cs.LG2026
Mapping and Measuring the Behavioral Evolution of Large Language Models
Dong Qiao, Chris Ding, Jicong Fan
Benchmark leaderboards summarize how well a language model performs, but not how its behavior relates to that of other models or changes across generations. We characterize the out…
cs.LG2026
CLUBench: A Clustering Benchmark
Feng Xiao, Dazhi Fu, Chris Ding +1
Clustering is a fundamental problem in data science with a long-standing research history, yielding numerous insightful algorithms. Despite this progress, a systematic and large-sc…