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cs.AI2026
LiveOIBench: Can Large Language Models Outperform Human Contestants in Informatics Olympiads?
Kaijian Zou, Aaron Xiong, Yunxiang Zhang +6
Competitive programming problems are increasingly used to evaluate the coding capabilities of large language models (LLMs) due to their complexity and ease of verification. Yet, cu…
cs.AI2026
AdaMEM: Test-Time Adaptive Memory for Language Agents
Yunxiang Zhang, Yiheng Li, Ali Payani +1
A central challenge for language agents is utilizing past experience to adapt to dynamic test-time conditions. While recent work demonstrates the promise of agentic memory mechanis…
cs.AI2026
Value-Conflict Diagnostics Reveal Widespread Alignment Faking in Language Models
Inderjeet Nair, Jie Ruan, Lu Wang
Alignment faking, where a model behaves aligned with developer policy when monitored but reverts to its own preferences when unobserved, is a concerning yet poorly understood pheno…