4 papers
Think Big, Search Small: Where Capacity Matters in Hierarchical Search Agents?
Qinnan Cai, Yibo Zhao, Xiang Li
Large language model based search agents increasingly adopt multi-agent architectures in which a main agent decomposes a complex question into sub-queries and dispatches them to pa…
Farewell to Item IDs: Unlocking the Scaling Potential of Large Ranking Models via Semantic Tokens
Zhen Zhao, Tong Zhang, Jie Xu +5
Recent studies on scaling up ranking models have achieved substantial improvement for recommendation systems and search engines. However, most large-scale ranking systems rely on i…
APEX: Academic Poster Editing Agentic Expert
Chengxin Shi, Qinnan Cai, Zeyuan Chen +5
Designing academic posters is a labor-intensive process requiring the precise balance of high-density content and sophisticated layout. While existing paper-to-poster generation me…
The Bias is in the Details: An Assessment of Cognitive Bias in LLMs
R. Alexander Knipper, Charles S. Knipper, Kaiqi Zhang +3
As Large Language Models (LLMs) are increasingly embedded in real-world decision-making processes, it becomes crucial to examine the extent to which they exhibit cognitive biases.…