most citedSecAlign: Defending Against Prompt Injection with Preference Optimization

17 citations

8 papers

cs.SE2025

Abstain and Validate: A Dual-LLM Policy for Reducing Noise in Agentic Program Repair

José Cambronero, Michele Tufano, Sherry Shi +7

Agentic Automated Program Repair (APR) is increasingly tackling complex, repository-level bugs in industry, but ultimately these patches still need to be reviewed by a human before…

cs.LG20254 cited

Synthetic Tabular Data: Methods, Attacks and Defenses

Graham Cormode, Samuel Maddock, Enayat Ullah +1

Synthetic data is often positioned as a solution to replace sensitive fixed-size datasets with a source of unlimited matching data, freed from privacy concerns. There has been much…

cs.PL2025

Gradual Metaprogramming

Tianyu Chen, Darshal Shetty, Jeremy G. Siek +4

Data engineers increasingly use domain-specific languages (DSLs) to generate the code for data pipelines. Such DSLs are often embedded in Python. Unfortunately, there are challenge…

cs.IR2025

Finding Interest Needle in Popularity Haystack: Improving Retrieval by Modeling Item Exposure

Rahul Agarwal, Amit Jaspal, Saurabh Gupta +1

Recommender systems operate in closed feedback loops, where user interactions reinforce popularity bias, leading to over-recommendation of already popular items while under-exposin…

cs.OS20259 cited

Coach: Exploiting Temporal Patterns for All-Resource Oversubscription in Cloud Platforms

Benjamin Reidys, Pantea Zardoshti, Íñigo Goiri +16

Cloud platforms remain underutilized despite multiple proposals to improve their utilization (e.g., disaggregation, harvesting, and oversubscription). Our characterization of the r…

cs.CR202417 cited

SecAlign: Defending Against Prompt Injection with Preference Optimization

Sizhe Chen, Arman Zharmagambetov, Saeed Mahloujifar +3

Large language models (LLMs) are becoming increasingly prevalent in modern software systems, interfacing between the user and the Internet to assist with tasks that require advance…