6 papers
Workspace Topology as an Attack Vector in Agentic Coding Assistants
Alexandre G. R. Day, Pradeep Yadlapalli, Sriram Venkatapathy +9
Agentic coding assistants are finding widespread use, not just in new code development but in quickly ingesting and leveraging third-party code. This opens up a risk of malicious c…
REPREC: Representation Driven Parameter-Efficient Recommendation System
Harshini Kavuru, Dwipam Katariya, Giri Iyengar +3
Large language models (LLMs) have been applied to sequential recommendation by formulating it as a natural language task. Previous work has improved personalization by incorporatin…
From Clicks to Intent: Cross-Platform Session Embeddings with LLM-Distilled Taxonomy for Financial Services Recommendations
Dianjing Fan, Yao Li, Kyaw Hpone Myint +4
Sequential user behavior modeling is widely adopted in industrial recommender systems; however, significant gaps remain in financial services, where pre-login web interactions and…
CoT-Guard: Small Models for Strong Monitoring
Nirav Diwan, Han Wang, Berkcan Kapusuzoglu +6
Monitoring the chain-of-thought (CoT) of reasoning models is a promising approach for detecting covert misbehavior (i.e., hidden objectives) in code generation tasks. While large m…
Towards Scalable Meta-Learning of near-optimal Interpretable Models via Synthetic Model Generations
Kyaw Hpone Myint, Zhe Wu, Alexandre G. R. Day +1
Decision trees are widely used in high-stakes fields like finance and healthcare due to their interpretability. This work introduces an efficient, scalable method for generating sy…
Enhancing Table Representations with LLM-powered Synthetic Data Generation
Dayu Yang, Natawut Monaikul, Amanda Ding +3
In the era of data-driven decision-making, accurate table-level representations and efficient table recommendation systems are becoming increasingly crucial for improving table man…