Papers
On the Transfer of Object-Centric Representation Learning
Aniket Rajiv Didolkar, Andrii Zadaianchuk, Anirudh Goyal et al.
Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference
Matthew Riemer, Gopeshh Subbaraj, Glen Berseth et al.
From Models to Microtheories: Distilling a Model's Topical Knowledge for Grounded Question-Answering
Nathaniel Weir, Bhavana Dalvi Mishra, Orion Weller et al.
Language Agents Meet Causality -- Bridging LLMs and Causal World Models
John Gkountouras, Matthias Lindemann, Phillip Lippe et al.
Tracing Representation Progression: Analyzing and Enhancing Layer-Wise Similarity
Jiachen Jiang, Jinxin Zhou, Zhihui Zhu
Unlocking Point Processes through Point Set Diffusion
David Lüdke, Enric Rabasseda Raventós, Marcel Kollovieh et al.
Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness
Boqian Wu, Qiao Xiao, Shunxin Wang et al.
Probing the Latent Hierarchical Structure of Data via Diffusion Models
Antonio Sclocchi, Alessandro Favero, Noam Itzhak Levi et al.
SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training
Tianjin Huang, Ziquan Zhu, Gaojie Jin et al.
OpenPRM: Building Open-domain Process-based Reward Models with Preference Trees
Kaiyan Zhang, Jiayuan Zhang, Haoxin Li et al.
IterGen: Iterative Semantic-aware Structured LLM Generation with Backtracking
Shubham Ugare, Rohan Gumaste, Tarun Suresh et al.
End-to-end Learning of Gaussian Mixture Priors for Diffusion Sampler
Denis Blessing, Xiaogang Jia, Gerhard Neumann
FlowDec: A flow-based full-band general audio codec with high perceptual quality
Simon Welker, Matthew Le, Ricky T. Q. Chen et al.
Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study
Shawn Tan, Songlin Yang, Aaron Courville et al.
Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy Hessians
Ishan Amin, Sanjeev Raja, Aditi S. Krishnapriyan
Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout
Bharat Srikishan, Daniel O'Malley, Mohamed Mehana et al.
Meta-Dynamical State Space Models for Integrative Neural Data Analysis
Ayesha Vermani, Josue Nassar, Hyungju Jeon et al.
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding
Taiwo Adebiyi, Bach Do, Ruda Zhang
InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation
Gaurav Sahu, Abhay Puri, Juan A. Rodriguez et al.
Measuring Non-Adversarial Reproduction of Training Data in Large Language Models
Michael Aerni, Javier Rando, Edoardo Debenedetti et al.
Scalable Extraction of Training Data from Aligned, Production Language Models
Milad Nasr, Javier Rando, Nicholas Carlini et al.
CONGO: Compressive Online Gradient Optimization
Jeremy Carleton, Prathik Vijaykumar, Divyanshu Saxena et al.
Support is All You Need for Certified VAE Training
Changming Xu, Debangshu Banerjee, Deepak Vasisht et al.
GeoLoRA: Geometric integration for parameter efficient fine-tuning
Steffen Schotthöfer, Emanuele Zangrando, Gianluca Ceruti et al.
Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups
Yuchen Zhu, Tianrong Chen, Lingkai Kong et al.