2 citations · 4 across the 9 of their papers we have counts for
5 papers · 1 filter
CaTS-Bench: Can Language Models Describe Time Series?
Luca Zhou, Pratham Yashwante, Marshall Fisher +4
Time series captioning, the task of describing time series in natural language, requires numeric and temporal reasoning, trend interpretation, and contextual understanding. Existin…
Video Unlearning via Low-Rank Refusal Vector
Simone Facchiano, Stefano Saravalle, Matteo Migliarini +7
Video generative models achieve high-quality synthesis from natural-language prompts by leveraging large-scale web data. However, this training paradigm inherently exposes them to…
LongCodeBench: Evaluating Coding LLMs at 1M Context Windows
Stefano Rando, Luca Romani, Alessio Sampieri +5
Context lengths for models have grown rapidly, from thousands to millions of tokens in just a few years. The extreme context sizes of modern long-context models have made it diffic…
Activation Patching for Interpretable Steering in Music Generation
Simone Facchiano, Giorgio Strano, Donato Crisostomi +4
Understanding how large audio models represent music, and using that understanding to steer generation, is both challenging and underexplored. Inspired by mechanistic interpretabil…
SeRpEnt: Selective Resampling for Expressive State Space Models
Stefano Rando, Luca Romani, Matteo Migliarini +3
State Space Models (SSMs) have recently enjoyed a rise to prominence in the field of deep learning for sequence modeling, especially as an alternative to Transformers. Their succes…