Papers
Research papers from arXiv and related sources
Misquoted No More: Securely Extracting F* Programs with IO
Shallow embeddings that use monads to represent effects are popular in proof-oriented languages because they are convenient for formal verification. Once shallowly embedded programs are verified, t...
Cezar-Constantin Andrici, Abigail Pribisova, Danel Ahman, Catalin Hritcu, Exequiel Rivas, Théo Wi...
ReAttn: Improving Attention-based Re-ranking via Attention Re-weighting
The strong capabilities of recent Large Language Models (LLMs) have made them highly effective for zero-shot re-ranking task. Attention-based re-ranking methods, which derive relevance scores direc...
Yuxing Tian, Fengran Mo, Weixu Zhang, Yiyan Qi, Jian-Yun Nie
Probabilistic Photonic Computing
Probabilistic computing excels in approximating combinatorial problems and modelling uncertainty. However, using conventional deterministic hardware for probabilistic models is challenging: (pseudo...
Frank Brückerhoff-Plückelmann, Anna P. Ovvyan, Akhil Varri, Hendrik Borras, Bernhard Klein, C. Da...
Leptophilic scalar dark matter in U(1)$_{L_μ-L_τ}$: Evading direct detection and prospective neutron star heating
Leptophilic dark matter (DM) is a well-motivated thermal WIMP framework that can evade stringent nuclear-recoil searches while remaining testable via DM-induced heating of neutron stars (NS). In th...
Chengfeng Cai, Hong-Hao Zhang
Multidimensional photonic computing
The rapidly increasing demands for computational throughput, bandwidth, and memory capacity fueled by breakthroughs in machine learning pose substantial challenges for conventional electronic compu...
Ivonne Bente, Shabnam Taheriniya, Francesco Lenzini, Frank Brückerhoff-Plückelmann, Michael Kues,...
Identification in Stochastic Choice
We characterize the identified sets of a wide range of stochastic choice models, including random utility, various models of boundedly-rational behavior, and dynamic discrete choice. In each of the...
Peter Caradonna, Christopher Turansick
Particle-like topologies of light in turbulent complex media
The basic building blocks of many forms of optical topologies are particle-like singularities in phase and polarisation, giving rise to lines of darkness that weave complex threads in 3D space. Alt...
Danilo Gomes Pires, Vasilios Cocotos, Cade Peters, Natalia M. Litchinitser, Andrew Forbes
Assessing Risks of Large Language Models in Mental Health Support: A Framework for Automated Clinical AI Red Teaming
Large Language Models (LLMs) are increasingly utilized for mental health support; however, current safety benchmarks often fail to detect the complex, longitudinal risks inherent in therapeutic dia...
Ian Steenstra, Paola Pedrelli, Weiyan Shi, Stacy Marsella, Timothy W. Bickmore
When Pretty Isn't Useful: Investigating Why Modern Text-to-Image Models Fail as Reliable Training Data Generators
Recent text-to-image (T2I) diffusion models produce visually stunning images and demonstrate excellent prompt following. But do they perform well as synthetic vision data generators? In this work, ...
Krzysztof Adamkiewicz, Brian Moser, Stanislav Frolov, Tobias Christian Nauen, Federico Raue, Andr...
Discover, Segment, and Select: A Progressive Mechanism for Zero-shot Camouflaged Object Segmentation
Current zero-shot Camouflaged Object Segmentation methods typically employ a two-stage pipeline (discover-then-segment): using MLLMs to obtain visual prompts, followed by SAM segmentation. However,...
Yilong Yang, Jianxin Tian, Shengchuan Zhang, Liujuan Cao
A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs
Sparse Mixture-of-Experts (SMoE) architectures are increasingly used to scale large language models efficiently, delivering strong accuracy under fixed compute budgets. However, SMoE models often s...
Zijie Liu, Jie Peng, Jinhao Duan, Zirui Liu, Kaixiong Zhou, Mingfu Liang, Luke Simon, Xi Liu, Zha...
Guiding Peptide Kinetics via Collective-Variable Tuning of Free-Energy Barriers
While recent advances in AI have transformed protein structure prediction, protein function is also often strongly influenced by the thermodynamic and kinetic features encoded in its underlying fre...
Alexander Zhilkin, Muralika Medaparambath, Dan Mendels
BeamVLM for Low-altitude Economy: Generative Beam Prediction via Vision-language Models
For low-altitude economy (LAE), fast and accurate beam prediction between high-mobility unmanned aerial vehicles (UAVs) and ground base stations is of paramount importance, which ensures seamless c...
Chenran Kou, Changsheng You, Mingjiang Wu, Dingzhu Wen, Zezhong Zhang, Chengwen Xing
Rethinking LoRA for Privacy-Preserving Federated Learning in Large Models
Fine-tuning large vision models (LVMs) and large language models (LLMs) under differentially private federated learning (DPFL) is hindered by a fundamental privacy-utility trade-off. Low-Rank Adapt...
Jin Liu, Yinbin Miao, Ning Xi, Junkang Liu
Janus-Q: End-to-End Event-Driven Trading via Hierarchical-Gated Reward Modeling
Financial market movements are often driven by discrete financial events conveyed through news, whose impacts are heterogeneous, abrupt, and difficult to capture under purely numerical prediction o...
Xiang Li, Zikai Wei, Yiyan Qi, Wanyun Zhou, Xiang Liu, Penglei Sun, Yongqi Zhang, Xiaowen Chu
Watson & Holmes: A Naturalistic Benchmark for Comparing Human and LLM Reasoning
Existing benchmarks for AI reasoning provide limited insight into how closely these capabilities resemble human reasoning in naturalistic contexts. We present an adaptation of the Watson & Holmes d...
Thatchawin Leelawat, Lewis D Griffin
Multi-Modal Representation Learning via Semi-Supervised Rate Reduction for Generalized Category Discovery
Generalized Category Discovery (GCD) aims to identify both known and unknown categories, with only partial labels given for the known categories, posing a challenging open-set recognition problem. ...
Wei He, Xianghan Meng, Zhiyuan Huang, Xianbiao Qi, Rong Xiao, Chun-Guang Li
Linearised Identification of Mechanical and Structural Anisotropy of Granular Materials from Hollow-Cylinder Experiments
Anisotropy in granular materials arises from both the internal fabric and the directionality of the stress state, yet separating these effects experimentally remains challenging. This study develop...
Mehdi Pouragha, Gertraud Medicus, Selvarajah Premnath, Siva Sivathayalan
Athena: An Autonomous Open-Hardware Tracked Rescue Robot Platform
In disaster response and situation assessment, robots have great potential in reducing the risks to the safety and health of first responders. As the situations encountered and the required capabil...
Stefan Fabian, Aljoscha Schmidt, Jonas Süß, Dishant, Aum Oza, Oskar von Stryk
DSDR: Dual-Scale Diversity Regularization for Exploration in LLM Reasoning
Reinforcement learning with verifiers (RLVR) is a central paradigm for improving large language model (LLM) reasoning, yet existing methods often suffer from limited exploration. Policies tend to c...
Zhongwei Wan, Yun Shen, Zhihao Dou, Donghao Zhou, Yu Zhang, Xin Wang, Hui Shen, Jing Xiong, Chaof...