Papers
Research papers from arXiv and related sources
A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic
Large language model (LLM)-based AI systems have shown promise for patient-facing diagnostic and management conversations in simulated settings. Translating these systems into clinical practice req...
Peter Brodeur, Jacob M. Koshy, Anil Palepu, Khaled Saab, Ava Homiar, Roma Ruparel, Charles Wu, Ry...
Efficient Policy Learning with Hybrid Evaluation-Based Genetic Programming for Uncertain Agile Earth Observation Satellite Scheduling
The Uncertain Agile Earth Observation Satellite Scheduling Problem (UAEOSSP) is a novel combinatorial optimization problem and a practical engineering challenge that aligns with the current demands...
Junhua Xue, Yuning Chen
Alfa: Attentive Low-Rank Filter Adaptation for Structure-Aware Cross-Domain Personalized Gaze Estimation
Pre-trained gaze models learn to identify useful patterns commonly found across users, but subtle user-specific variations (i.e., eyelid shape or facial structure) can degrade model performance. Te...
He-Yen Hsieh, Wei-Te Mark Ting, H. T. Kung
LLM-Driven Online Aggregation for Unstructured Text Analytics
Large Language Models (LLMs) exhibit strong capabilities in text processing, and recent research has augmented SQL and DataFrame with LLM-powered semantic operators for data analysis. However, LLM-...
Chao Hui, Weizheng Lu, Yanjie Gao, Lingfeng Xiong, Yunhai Wang, Yueguo Chen
Splitting methods for the Gross-Pitaevskii equation on the full space and vortex nucleation
We prove the convergence in Zhidkov spaces of the first-order Lie-Trotter and the second-order Strang splitting schemes for the time integration of the Gross-Pitaesvkii equation with a time-depende...
Quentin Chauleur, Gaspard Kemlin
Robust ellipticity measurements of 29 Galactic globular clusters
Globular clusters (GCs) exhibit varying degrees of flattening (ellipticity), which may provide insight into their internal dynamics and evolution histories. Commonly used methods to measure ellipti...
Laurane Fréour, Ellen Leitinger, Elena Pancino, Alice Zocchi, Glenn van de Ven
One Model Is Enough: Native Retrieval Embeddings from LLM Agent Hidden States
LLM agents that retrieve external knowledge typically generate a search query as text, then run a separate embedding model to encode it into a vector. This two-model pipeline adds infrastructure co...
Bo Jiang
IronEngine: Towards General AI Assistant
This paper presents IronEngine, a general AI assistant platform organized around a unified orchestration core that connects a desktop user interface, REST and WebSocket APIs, Python clients, local ...
Xi Mo
SYNAPSE: Framework for Neuron Analysis and Perturbation in Sequence Encoding
In recent years, Artificial Intelligence has become a powerful partner for complex tasks such as data analysis, prediction, and problem-solving, yet its lack of transparency raises concerns about i...
Jesús Sánchez Ochoa, Enrique Tomás Martínez Beltrán, Alberto Huertas Celdrán
Human-Aware Robot Behaviour in Self-Driving Labs
Self-driving laboratories (SDLs) are rapidly transforming research in chemistry and materials science to accelerate new discoveries. Mobile robot chemists (MRCs) play a pivotal role by autonomously...
Satheeshkumar Veeramani, Anna Kisil, Abigail Bentley, Hatem Fakhruldeen, Gabriella Pizzuto, Andre...
Aligning to Illusions: Choice Blindness in Human and AI Feedback
Reinforcement Learning from Human Feedback (RLHF) assumes annotator preferences reflect stable internal states. We challenge this through three experiments spanning the preference pipeline. In a hu...
Wenbin Wu
Sandpiper: Orchestrated AI-Annotation for Educational Discourse at Scale
Digital educational environments are expanding toward complex AI and human discourse, providing researchers with an abundance of data that offers deep insights into learning and instructional proce...
Daryl Hedley, Doug Pietrzak, Jorge Dias, Ian Burden, Bakhtawar Ahtisham, Zhuqian Zhou, Kirk Vanac...
Revealing Behavioral Plasticity in Large Language Models: A Token-Conditional Perspective
In this work, we reveal that Large Language Models (LLMs) possess intrinsic behavioral plasticity-akin to chameleons adapting their coloration to environmental cues-that can be exposed through toke...
Liyuan Mao, Le Yu, Jing Zhou, Chujie Zheng, Bowen Yu, Chang Gao, Shixuan Liu, An Yang, Weinan Zha...
NLE: Non-autoregressive LLM-based ASR by Transcript Editing
While autoregressive (AR) LLM-based ASR systems achieve strong accuracy, their sequential decoding limits parallelism and incurs high latency. We propose NLE, a non-autoregressive (NAR) approach th...
Avihu Dekel, Samuel Thomas, Takashi Fukada, George Saon
COACH meets QUORUM: A Framework and Pipeline for Aligning User, Expert and Developer Perspectives in LLM-generated Health Counselling
Systems that collect data on sleep, mood, and activities can provide valuable lifestyle counselling to populations affected by chronic disease and its consequences. Such systems are, however, chall...
Yee Man Ng, Bram van Dijk, Pieter Beynen, Otto Boekesteijn, Joris Jansen, Gerard van Oortmerssen,...
Adaptive Loops and Memory in Transformers: Think Harder or Know More?
Chain-of-thought (CoT) prompting enables reasoning in language models but requires explicit verbalization of intermediate steps. Looped transformers offer an alternative by iteratively refining rep...
Markus Frey, Behzad Shomali, Ali Hamza Bashir, David Berghaus, Mehdi Ali
A Hierarchical Error-Corrective Graph Framework for Autonomous Agents with LLM-Based Action Generation
We propose a Hierarchical Error-Corrective Graph FrameworkforAutonomousAgentswithLLM-BasedActionGeneration(HECG),whichincorporates three core innovations: (1) Multi-Dimensional Transferable Strateg...
Cong Cao, Jingyao Zhang, Kun Tong
AULLM++: Structural Reasoning with Large Language Models for Micro-Expression Recognition
Micro-expression Action Unit (AU) detection identifies localized AUs from subtle facial muscle activations, providing a foundation for decoding affective cues. Previous methods face three key limit...
Zhishu Liu, Kaishen Yuan, Bo Zhao, Hui Ma, Zitong Yu
Rectified flow-based prediction of post-treatment brain MRI from pre-radiotherapy priors for patients with glioma
Purpose/Objective: Brain tumors result in 20 years of lost life on average. Standard therapies induce complex structural changes in the brain that are monitored through MRI. Recent developments in ...
Selena Huisman, Nordin Belkacemi, Vera Keil, Joost Verhoeff, Szabolcs David
Leaderboard Incentives: Model Rankings under Strategic Post-Training
Influential benchmarks incentivize competing model developers to strategically allocate post-training resources toward improvements on the leaderboard, a phenomenon dubbed benchmaxxing or training ...
Yatong Chen, Guanhua Zhang, Moritz Hardt