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MatrAIx: Simulating the World with 8.3 Billion Persona Agents
Xiaomin Li, Yuexing Hao, Jianheng Hou +90
Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…
WorldMemArena: Evaluating Multimodal Agent Memory Through Action-World Interaction
Chengzhi Liu, Yuzhe Yang, Sophia Xiao Pu +14
Multimodal large language models are increasingly deployed as long-horizon agents, where memory must do more than recall: it must track an evolving world, revise what has gone stal…
ReasonOps: Operator Segmentation for LLM Reasoning Traces
Daniel Lee, Owen Queen, James Zou
Chain-of-thought traces from large reasoning models can span tens of thousands of tokens, yet we lack a vocabulary for describing their internal structure. Previous methods develop…
Synthetic Mixed Training: Scaling Parametric Knowledge Acquisition Beyond RAG
Seungju Han, Konwoo Kim, Chanwoo Park +5
Synthetic data augmentation helps language models learn new knowledge in data-constrained domains. However, naively scaling existing synthetic data methods by training on more synt…
The Price Reversal Phenomenon: When Cheaper Reasoning Models Cost More
Lingjiao Chen, Chi Zhang, Yeye He +3
Developers and consumers increasingly choose reasoning models (RMs) based on their listed API prices. However, how accurately do these prices reflect actual inference costs? We con…