7 citations · 8 across the 7 of their papers we have counts for
7 papers
Where Hindsight Credit Can Reside: A Signed-Capacity View of Token Updates in RLVR
Yuhang He, Haodong Wu, Siyi Liu +7
Reinforcement Learning with Verifiable Rewards (RLVR) improves the reasoning ability of Large Language Models (LLMs), but sparse outcome rewards make token-level credit assignment…
ExeKGLib: A Platform for Machine Learning Analytics based on Knowledge Graphs
Antonis Klironomos, Baifan Zhou, Zhipeng Tan +4
Nowadays machine learning (ML) practitioners have access to numerous ML libraries available online. Such libraries can be used to create ML pipelines that consist of a series of st…
ReaLitE: Enrichment of Relation Embeddings in Knowledge Graphs using Numeric Literals
Antonis Klironomos, Baifan Zhou, Zhuoxun Zheng +3
Most knowledge graph embedding (KGE) methods tailored for link prediction focus on the entities and relations in the graph, giving little attention to other literal values, which m…
Literal-Aware Knowledge Graph Embedding for Welding Quality Monitoring: A Bosch Case
Zhipeng Tan, Baifan Zhou, Zhuoxun Zheng +5
Recently there has been a series of studies in knowledge graph embedding (KGE), which attempts to learn the embeddings of the entities and relations as numerical vectors and mathem…
Scaling Data Science Solutions with Semantics and Machine Learning: Bosch Case
Baifan Zhou, Nikolay Nikolov, Zhuoxun Zheng +5
Industry 4.0 and Internet of Things (IoT) technologies unlock unprecedented amount of data from factory production, posing big data challenges in volume and variety. In that contex…
ExeKGLib: Knowledge Graphs-Empowered Machine Learning Analytics
Antonis Klironomos, Baifan Zhou, Zhipeng Tan +4
Many machine learning (ML) libraries are accessible online for ML practitioners. Typical ML pipelines are complex and consist of a series of steps, each of them invoking several ML…