23 citations · 30 across the 19 of their papers we have counts for
6 papers · 1 filter
Incorporating Spatial Information into Goal-Conditioned Hierarchical Reinforcement Learning via Graph Representations
Shuyuan Zhang, Zihan Wang, Xiao-Wen Chang +1
The integration of graphs with Goal-conditioned Hierarchical Reinforcement Learning (GCHRL) has recently gained attention, as intermediate goals (subgoals) can be effectively sampl…
AetherCode: Evaluating LLMs' Ability to Win In Premier Programming Competitions
Zihan Wang, Jiaze Chen, Zhicheng Liu +25
Competitive programming has emerged as a critical benchmark for evaluating the reasoning and coding capabilities of Large Language Models (LLMs). Despite impressive progress on exi…
Multi-dimensional Autoscaling of Processing Services: A Comparison of Agent-based Methods
Boris Sedlak, Alireza Furutanpey, Zihang Wang +2
Edge computing breaks with traditional autoscaling due to strict resource constraints, thus, motivating more flexible scaling behaviors using multiple elasticity dimensions. This w…
MedGUIDE: Benchmarking Clinical Decision-Making in Large Language Models
Xiaomin Li, Mingye Gao, Yuexing Hao +4
Clinical guidelines, typically structured as decision trees, are central to evidence-based medical practice and critical for ensuring safe and accurate diagnostic decision-making.…
KEIR @ ECIR 2025: The Second Workshop on Knowledge-Enhanced Information Retrieval
Zihan Wang, Jinyuan Fang, Giacomo Frisoni +4
Pretrained language models (PLMs) like BERT and GPT-4 have become the foundation for modern information retrieval (IR) systems. However, existing PLM-based IR models primarily rely…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1168
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…