9 citations · 10 across the 8 of their papers we have counts for
9 papers
Interactive-Policy Distillation with Bidirectional Propose-and-Verify
Shutong Wu, Xiwen Chen, Brendan Rappazzo +4
On-policy distillation (OPD) trains a student model on its self-generated trajectories with dense token-level teacher feedback. However, naive OPD may suffer from teacher unanchori…
S-SPPO: Semantic-Calibrated Self-Play Preference Optimization
Xiwen Chen, Wenhui Zhu, Jingjing Wang +13
Aligning Large Language Models (LLMs) with human preferences is often formulated via Direct Preference Optimization (DPO). However, the standard Bradley-Terry instantiation of DPO…
AriadneMem: Threading the Maze of Lifelong Memory for LLM Agents
Wenhui Zhu, Xiwen Chen, Zhipeng Wang +11
Long-horizon LLM agents require memory systems that remain accurate under fixed context budgets. However, existing systems struggle with two persistent challenges in long-term dial…
Learning to Reason with Mixture of Tokens
Adit Jain, Brendan Rappazzo
Reinforcement learning with verifiable rewards (RLVR) has become a leading approach for improving large language model (LLM) reasoning capabilities. Most current methods follow var…
GEM-RAG: Graphical Eigen Memories For Retrieval Augmented Generation
Brendan Hogan Rappazzo, Yingheng Wang, Aaron Ferber +1
The ability to form, retrieve, and reason about memories in response to stimuli serves as the cornerstone for general intelligence - shaping entities capable of learning, adaptatio…
Critic Loss for Image Classification
Brendan Hogan Rappazzo, Aaron Ferber, Carla Gomes
Modern neural network classifiers achieve remarkable performance across a variety of tasks; however, they frequently exhibit overconfidence in their predictions due to the cross-en…
Automatic Detection and Compression for Passive Acoustic Monitoring of the African Forest Elephant
Johan Bjorck, Brendan H. Rappazzo, Di Chen +3
In this work, we consider applying machine learning to the analysis and compression of audio signals in the context of monitoring elephants in sub-Saharan Africa. Earth's biodivers…
Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery
Yexiang Xue, Junwen Bai, Ronan Le Bras +8
High-Throughput materials discovery involves the rapid synthesis, measurement, and characterization of many different but structurally-related materials. A key problem in materials…
Automated Phase Mapping with AgileFD and its Application to Light Absorber Discovery in the V-Mn-Nb Oxide System
Santosh K. Suram, Yexiang Xue, Junwen Bai +8
Rapid construction of phase diagrams is a central tenet of combinatorial materials science with accelerated materials discovery efforts often hampered by challenges in interpreting…