Ax Kushal Agrawal, Frank Xiao, Guido Bergman, Asa Cooper Stickland 4/24/2026

Why Do Language Model Agents Whistleblow?

Studies why LLM agents disclose information to external parties contrary to user instructions, examining alignment behavior.

Ax Kevin Stowe, Svetlana Afanaseva, Rodolfo Raimundo, Yitao Sun, Kailash Patil 4/24/2026

Identifying Bias in Machine-generated Text Detection

Study identifying and characterizing biases in machine-generated text detection systems across different text types and domains.

Ax Jiaying Zhang, Lei Shi, Jiguo Li, Jun Xu, Jiuchong Gao, Jinghua Hao, Renqing He 4/24/2026

GeoRA: Geometry-Aware Low-Rank Adaptation for RLVR

Parameter-efficient adaptation method preserving geometric structure of pre-trained models during reinforcement learning with verifiable rewards.

Ax Binglei Lou, Haoran Wu, Kevin Lau, Gregor MacDonald, Jiayi Nie, Yao Lai, Can Xiao, Xuan Guo, Jianyi Cheng, Rika Antonova, Robert Mullins, Aaron Zhao 4/24/2026

NPU Design for Diffusion Language Model Inference

NPU architecture design optimized for diffusion-based LLM inference with bidirectional attention and block-wise KV cache patterns.

Ax Muhammad Ahmed Mohsin, Muhammad Umer, Ahsan Bilal, Zihao He, Muhammad Usman Rafique, Asad Aali, Muhammad Ali Jamshed, John M. Cioffi, Emily Fox 4/24/2026

Continuous-Utility Direct Preference Optimization

Framework replacing binary preference labels with continuous utility scores for fine-grained alignment of LLM reasoning capabilities.

Ax Markus Knauer, Edoardo Fiorini, Maximilian M\"uhlbauer, Stefan Schneyer, Promwat Angsuratanawech, Florian Samuel Lay, Timo Bachmann, Samuel Bustamante, Korbinian Nottensteiner, Freek Stulp, Alin Albu-Sch\"affer, Jo\~ao Silv\'erio, Thomas Eiband 4/24/2026

MOMO: A framework for seamless physical, verbal, and graphical robot skill learning and adaptation

Interactive framework enabling industrial robot skill adaptation through kinesthetic, natural language, and graphical interaction modalities.

Ax Markus Knauer, Edoardo Fiorini, Maximilian M\"uhlbauer, Stefan Schneyer, Promwat Angsuratanawech, Florian Samuel Lay, Timo Bachmann, Samuel Bustamante, Korbinian Nottensteiner, Freek Stulp, Alin Albu-Sch\"affer, Jo\~ao Silv\'erio, Thomas Eiband 4/24/2026

MOMO: A framework for seamless physical, verbal, and graphical robot skill learning and adaptation

Interactive framework enabling industrial robot skill adaptation through kinesthetic, natural language, and graphical interaction modalities.