7 citations · 13 across the 12 of their papers we have counts for
6 papers · 1 filter
Inference-Time Personalized Alignment with a Few User Preference Queries
Victor-Alexandru Pădurean, Parameswaran Kamalaruban, Nachiket Kotalwar +2
We study the problem of aligning a generative model's response with a user's preferences. Recent works have proposed several different formulations for personalized alignment; howe…
Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation
Nachiket Kotalwar, Alkis Gotovos, Adish Singla
Generative AI and large language models hold great promise in enhancing programming education by generating individualized feedback and hints for learners. Recent works have primar…
On the Existence of Universal Lottery Tickets
Rebekka Burkholz, Nilanjana Laha, Rajarshi Mukherjee +1
The lottery ticket hypothesis conjectures the existence of sparse subnetworks of large randomly initialized deep neural networks that can be successfully trained in isolation. Rece…
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification
Alkis Gotovos, Rebekka Burkholz, John Quackenbush +1
Modeling the time evolution of discrete sets of items (e.g., genetic mutations) is a fundamental problem in many biomedical applications. We approach this problem through the lens…
Strong Log-Concavity Does Not Imply Log-Submodularity
Alkis Gotovos
We disprove a recent conjecture regarding discrete distributions and their generating polynomials stating that strong log-concavity implies log-submodularity.
Discrete Sampling using Semigradient-based Product Mixtures
Alkis Gotovos, Hamed Hassani, Andreas Krause +1
We consider the problem of inference in discrete probabilistic models, that is, distributions over subsets of a finite ground set. These encompass a range of well-known models in m…