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researcher

Philip Treleaven

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.CL1
  • cs.LG1
  • q-fin.TR1
ORCID 0000-0001-8803-8297

identity via Semantic Scholar / OpenAlex

activity
20222025
most citedMachine Learning Modeling to Evaluate the Value of Football Players

2 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

cs.AI2025

Mind the Gap: Comparing Model- vs Agentic-Level Red Teaming with Action-Graph Observability on GPT-OSS-20B

Ilham Wicaksono, Zekun Wu, Rahul Patel +3

As the industry increasingly adopts agentic AI systems, understanding their unique vulnerabilities becomes critical. Prior research suggests that security flaws at the model level…

cs.CL2025

Cultural Alignment in Large Language Models Using Soft Prompt Tuning

Reem I. Masoud, Martin Ferianc, Philip Treleaven +1

Large Language Model (LLM) alignment conventionally relies on supervised fine-tuning or reinforcement learning based alignment frameworks. These methods typically require labeled o…

q-fin.TR2024

Limit Order Book Simulations: A Review

Konark Jain, Nick Firoozye, Jonathan Kochems +1

Limit Order Books (LOBs) serve as a mechanism for buyers and sellers to interact with each other in the financial markets. Modelling and simulating LOBs is quite often necessary fo…

cs.LG2022★ 2 cited

Machine Learning Modeling to Evaluate the Value of Football Players

Chenyao Li, Stylianos Kampakis, Philip Treleaven

In most sports, especially football, most coaches and analysts search for key performance indicators using notational analysis. This method utilizes a statistical summary of events…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.