Papers
On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery
Renpu Liu, Ruida Zhou, Cong Shen et al.
Towards Automated Knowledge Integration From Human-Interpretable Representations
Kasia Kobalczyk, Mihaela van der Schaar
AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs
Xiaogeng Liu, Peiran Li, G. Edward Suh et al.
Causal Representation Learning from Multimodal Biomedical Observations
Yuewen Sun, Lingjing Kong, Guangyi Chen et al.
Learn-by-interact: A Data-Centric Framework For Self-Adaptive Agents in Realistic Environments
Hongjin SU, Ruoxi Sun, Jinsung Yoon et al.
Progressive Compression with Universally Quantized Diffusion Models
Yibo Yang, Justus Will, Stephan Mandt
Robotouille: An Asynchronous Planning Benchmark for LLM Agents
Gonzalo Gonzalez-Pumariega, Leong Su Yean, Neha Sunkara et al.
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks
Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman
Self-Attention-Based Contextual Modulation Improves Neural System Identification
Isaac Lin, Tianye Wang, Shang Gao et al.
Can We Trust Embodied Agents? Exploring Backdoor Attacks against Embodied LLM-Based Decision-Making Systems
Ruochen Jiao, Shaoyuan Xie, Justin Yue et al.
Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
Zijian Liu, Zhengyuan Zhou
Training Neural Networks as Recognizers of Formal Languages
Alexandra Butoi, Ghazal Khalighinejad, Anej Svete et al.
Is uniform expressivity too restrictive? Towards efficient expressivity of GNNs
Sammy Khalife, Josué Tonelli-Cueto
Transformers Struggle to Learn to Search
Abulhair Saparov, Srushti Ajay Pawar, Shreyas Pimpalgaonkar et al.
Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement
Bryan Bo Cao, Lawrence O'Gorman, Michael Coss et al.
Multi-agent cooperation through learning-aware policy gradients
Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald et al.
Flow-based Variational Mutual Information: Fast and Flexible Approximations
Caleb Dahlke, Jason Pacheco
ReGen: Generative Robot Simulation via Inverse Design
Phat Tan Nguyen, Tsun-Hsuan Wang, Zhang-Wei Hong et al.
Score-based free-form architectures for high-dimensional Fokker-Planck equations
Feng Liu, Faguo Wu, Xiao Zhang
ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities
Ezra Karger, Houtan Bastani, Chen Yueh-Han et al.
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