Papers
WeGeFT: Weight-Generative Fine-Tuning for Multi-Faceted Efficient Adaptation of Large Models
Chinmay Savadikar, Xi Song, Tianfu Wu
Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
Davide Sartor, Alberto Sinigaglia, Gian Antonio Susto
The underlying structures of self-attention: symmetry, directionality, and emergent dynamics in Transformer training
Matteo Saponati, Pascal Josef Sager, Pau Vilimelis Aceituno et al.
Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting
Sunny Sanyal, Hayden Prairie, Rudrajit Das et al.
The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes
Pedro Pinto Santos, Alberto Sardinha, Francisco S. Melo
$∞$-Video: A Training-Free Approach to Long Video Understanding via Continuous-Time Memory Consolidation
Saul Santos, António Farinhas, Daniel C Mcnamee et al.
MGD$^3$ : Mode-Guided Dataset Distillation using Diffusion Models
Jeffrey A Chan Santiago, Praveen Tirupattur, Gaurav Kumar Nayak et al.
Collapse-Proof Non-Contrastive Self-Supervised Learning
Emanuele Sansone, Tim Lebailly, Tinne Tuytelaars
Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization
Suryanarayana Sankagiri, Jalal Etesami, Matthias Grossglauser
Joint Learning of Energy-based Models and their Partition Function
Michael Eli Sander, Vincent Roulet, Tianlin Liu et al.
SENSEI: Semantic Exploration Guided by Foundation Models to Learn Versatile World Models
Cansu Sancaktar, Christian Gumbsch, Andrii Zadaianchuk et al.
Tuning LLM Judge Design Decisions for 1/1000 of the Cost
David Salinas, Omar Swelam, Frank Hutter
Benign Overfitting in Token Selection of Attention Mechanism
Keitaro Sakamoto, Issei Sato
LGDM: Latent Guidance in Diffusion Models for Perceptual Evaluations
Shreshth Saini, Ru-Ling Liao, Yan Ye et al.
The Diffusion Duality
Subham Sekhar Sahoo, Justin Deschenaux, Aaron Gokaslan et al.
Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge
Swarnadeep Saha, Xian Li, Marjan Ghazvininejad et al.
Dueling Convex Optimization with General Preferences
Aadirupa Saha, Tomer Koren, Yishay Mansour
Adversarial Reasoning at Jailbreaking Time
Mahdi Sabbaghi, Paul Kassianik, George J. Pappas et al.
Disparate Conditional Prediction in Multiclass Classifiers
Sivan Sabato, Eran Treister, Elad Yom-Tov
An Architecture Search Framework for Inference-Time Techniques
Jon Saad-Falcon, Adrian Gamarra Lafuente, Shlok Natarajan et al.
A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation
Jongha Jon Ryu, Abhin Shah, Gregory W. Wornell
Value-Based Deep RL Scales Predictably
Oleh Rybkin, Michal Nauman, Preston Fu et al.
Adaptive Exploration for Multi-Reward Multi-Policy Evaluation
Alessio Russo, Aldo Pacchiano
Zero-Shot Offline Imitation Learning via Optimal Transport
Thomas Rupf, Marco Bagatella, Nico Gürtler et al.
LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations
Anian Ruoss, Fabio Pardo, Harris Chan et al.