19 citations · 30 across the 21 of their papers we have counts for
7 papers · 1 filter
CTkvr: KV Cache Retrieval for Long-Context LLMs via Centroid then Token Indexing
Kuan Lu, Shuhang Lin, Sai Wu +7
Large language models (LLMs) are increasingly applied in long-context scenarios such as multi-turn conversations. However, long contexts pose significant challenges for inference e…
ORIGAMISPACE: Benchmarking Multimodal LLMs in Multi-Step Spatial Reasoning with Mathematical Constraints
Rui Xu, Dakuan Lu, Zicheng Zhao +5
Spatial reasoning is a key capability in the field of artificial intelligence, especially crucial in areas such as robotics, computer vision, and natural language understanding. Ho…
Reflective Personalization Optimization: A Post-hoc Rewriting Framework for Black-Box Large Language Models
Teqi Hao, Xioayu Tan, Shaojie Shi +2
The personalization of black-box large language models (LLMs) is a critical yet challenging task. Existing approaches predominantly rely on context injection, where user history is…
ChemAmp: Amplified Chemistry Tools via Composable Agents
Zhucong Li, Powei Chang, Jin Xiao +6
Although LLM-based agents are proven to master tool orchestration in scientific fields, particularly chemistry, their single-task performance remains limited by underlying tool con…
Guess What I am Thinking: A Benchmark for Inner Thought Reasoning of Role-Playing Language Agents
Rui Xu, MingYu Wang, XinTao Wang +4
Recent advances in LLM-based role-playing language agents (RPLAs) have attracted broad attention in various applications. While chain-of-thought reasoning has shown importance in m…
AURORA:Automated Training Framework of Universal Process Reward Models via Ensemble Prompting and Reverse Verification
Xiaoyu Tan, Tianchu Yao, Chao Qu +8
The reasoning capabilities of advanced large language models (LLMs) like o1 have revolutionized artificial intelligence applications. Nevertheless, evaluating and optimizing comple…
SCP-116K: A High-Quality Problem-Solution Dataset and a Generalized Pipeline for Automated Extraction in the Higher Education Science Domain
Dakuan Lu, Xiaoyu Tan, Rui Xu +5
Recent breakthroughs in large language models (LLMs) exemplified by the impressive mathematical and scientific reasoning capabilities of the o1 model have spotlighted the critical…