6 papers · 1 filter
Form Over Content In Gradient-Based Data Attribution Methods
Sunwoo Kim, Seokwon Jung, Sohyung Kim +2
Data attribution methods using gradient similarity are widely used to analyze and select training data for large language models, but what gradient similarity actually measures is…
MuPPET: A Benchmark for Contextual Privacy of LLM Assistants in Multi-Party Conversations
Elena Sofia Ruzzetti, Cornelius Emde, Sangdoo Yun +2
LLM agents are increasingly deployed in multi-party environments, handling sensitive personal data on behalf of individual users, for instance in group chats. When such an agent di…
Privacy Collapse: Benign Fine-Tuning Can Break Contextual Privacy in Language Models
Anmol Goel, Cornelius Emde, Sangdoo Yun +2
We identify a novel phenomenon in language models: benign fine-tuning of frontier models can lead to privacy collapse. We find that diverse, subtle patterns in training data can de…
Dr.LLM: Dynamic Layer Routing in LLMs
Ahmed Heakl, Martin Gubri, Salman Khan +2
Large Language Models (LLMs) process every token through all layers of a transformer stack, causing wasted computation on simple queries and insufficient flexibility for harder one…
Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers
Tommaso Green, Martin Gubri, Haritz Puerto +2
We study privacy leakage in the reasoning traces of large reasoning models used as personal agents. Unlike final outputs, reasoning traces are often assumed to be internal and safe…
C-SEO Bench: Does Conversational SEO Work?
Haritz Puerto, Martin Gubri, Tommaso Green +2
Large Language Models (LLMs) are transforming search engines into Conversational Search Engines (CSE). Consequently, Search Engine Optimization (SEO) is being shifted into Conversa…