33 citations · 42 across the 4 of their papers we have counts for
4 papers
DISC: Dynamic Decomposition Improves LLM Inference Scaling
Jonathan Light, Wei Cheng, Benjamin Riviere +6
Inference scaling methods for LLMs often rely on decomposing problems into steps (or groups of tokens), followed by sampling and selecting the best next steps. However, these steps…
POLAR: Preference Optimization and Learning Algorithms for Robotics
Maegan Tucker, Kejun Li, Yisong Yue +1
Parameter tuning for robotic systems is a time-consuming and challenging task that often relies on domain expertise of the human operator. Moreover, existing learning methods are n…
The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions
Jennifer J. Sun, Tomomi Karigo, Dipam Chakraborty +8
Multi-agent behavior modeling aims to understand the interactions that occur between agents. We present a multi-agent dataset from behavioral neuroscience, the Caltech Mouse Social…
Detecting Adversarial Examples via Neural Fingerprinting
Sumanth Dathathri, Stephan Zheng, Tianwei Yin +2
Deep neural networks are vulnerable to adversarial examples, which dramatically alter model output using small input changes. We propose Neural Fingerprinting, a simple, yet effect…