Papers
Research papers from arXiv and related sources
Interpreting and Steering State-Space Models via Activation Subspace Bottlenecks
State-space models (SSMs) have emerged as an efficient strategy for building powerful language models, avoiding the quadratic complexity of computing attention in transformers. Despite their promis...
Vamshi Sunku Mohan, Kaustubh Gupta, Aneesha Das, Chandan Singh
RLHFless: Serverless Computing for Efficient RLHF
Reinforcement Learning from Human Feedback (RLHF) has been widely applied to Large Language Model (LLM) post-training to align model outputs with human preferences. Recent models, such as DeepSeek-...
Rui Wei, Hanfei Yu, Shubham Jain, Yogarajan Sivakumar, Devesh Tiwari, Jian Li, Seung-Jong Park, H...
IRSDE-Despeckle: A Physics-Grounded Diffusion Model for Generalizable Ultrasound Despeckling
Ultrasound imaging is widely used for real-time, noninvasive diagnosis, but speckle and related artifacts reduce image quality and can hinder interpretation. We present a diffusion-based ultrasound...
Shuoqi Chen, Yujia Wu, Geoffrey P. Luke
SoPE: Spherical Coordinate-Based Positional Embedding for Enhancing Spatial Perception of 3D LVLMs
3D Large Vision-Language Models (3D LVLMs) built upon Large Language Models (LLMs) have achieved remarkable progress across various multimodal tasks. However, their inherited position-dependent mod...
Guanting Ye, Qiyan Zhao, Wenhao Yu, Liangyu Yuan, Mingkai Li, Xiaofeng Zhang, Jianmin Ji, Yanyong...
Opacity in Discrete Event Systems: A Perspective and Overview
Opacity has emerged as a central confidentiality notion for information-flow security in discrete event systems (DES), capturing the requirement that an external observer (intruder) should never be...
Xiang Yin
Same Words, Different Judgments: Modality Effects on Preference Alignment
Preference-based reinforcement learning (PbRL) is the dominant framework for aligning AI systems to human preferences, but its application to speech remains underexplored. We present a controlled c...
Aaron Broukhim, Nadir Weibel, Eshin Jolly
LLM-driven discovery for carbon allotropes with bond-network entropy
The discovery of novel carbon allotropes with tailored thermal and mechanical properties is critical for advanced thermal management. However, exploring the vast configurational space of carbon usi...
Yuzhou Hao, Yujie Liu, Xuejie Li, Turab Lookman, Xiangdong Ding, Jun Sun, Zhibin Gao
IMMACULATE: A Practical LLM Auditing Framework via Verifiable Computation
Commercial large language models are typically deployed as black-box API services, requiring users to trust providers to execute inference correctly and report token usage honestly. We present IMMA...
Yanpei Guo, Wenjie Qu, Linyu Wu, Shengfang Zhai, Lionel Z. Wang, Ming Xu, Yue Liu, Binhang Yuan, ...
Tokenization, Fusion and Decoupling: Bridging the Granularity Mismatch Between Large Language Models and Knowledge Graphs
Leveraging Large Language Models (LLMs) for Knowledge Graph Completion (KGC) is promising but hindered by a fundamental granularity mismatch. LLMs operate on fragmented token sequences, whereas ent...
Siyue Su, Jian Yang, Bo Li, Guanglin Niu
Reinforcing Real-world Service Agents: Balancing Utility and Cost in Task-oriented Dialogue
The rapid evolution of Large Language Models (LLMs) has accelerated the transition from conversational chatbots to general agents. However, effectively balancing empathetic communication with budge...
Ning Gao, Wei Zhang, Yuqin Dai, Ling Shi, Ziyin Wang, Yujie Wang, Wei He, Jinpeng Wang, Chaozheng...
Ideal random quantum circuits pass the LXEB test
We show that noiseless random quantum circuits pass the linear cross-entropy benchmark (LXEB) test with high probability. If the circuits are linear depth, and thus form unitary 4-designs, the LXEB...
Nicholas Hunter-Jones, Jonas Haferkamp
Learning about Corner Kicks in Soccer by Analysis of Event Times Using a Frailty Model
Corner kicks are an important event in soccer because they are often the result of strong attacking play and can be of keen interest to sports fans and bettors. Peng, Hu, and Swartz (2024, Computat...
Riley L Isaacs, X. Joan Hu, K. Ken Peng, Tim Swartz
SUPERGLASSES: Benchmarking Vision Language Models as Intelligent Agents for AI Smart Glasses
The rapid advancement of AI-powered smart glasses, one of the hottest wearable devices, has unlocked new frontiers for multimodal interaction, with Visual Question Answering (VQA) over external kno...
Zhuohang Jiang, Xu Yuan, Haohao Qu, Shanru Lin, Kanglong Liu, Wenqi Fan, Qing Li
Accelerating LLM Pre-Training through Flat-Direction Dynamics Enhancement
Pre-training Large Language Models requires immense computational resources, making optimizer efficiency essential. The optimization landscape is highly anisotropic, with loss reduction driven pred...
Shuchen Zhu, Rizhen Hu, Mingze Wang, Mou Sun, Xue Wang, Kun Yuan, Zaiwen Wen
Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directions
Large language models have enabled agents that reason, plan, and interact with tools and environments to accomplish complex tasks. As these agents operate over extended interaction horizons, their ...
Yue Xu, Qian Chen, Zizhan Ma, Dongrui Liu, Wenxuan Wang, Xiting Wang, Li Xiong, Wenjie Wang
Forecasting Antimicrobial Resistance Trends Using Machine Learning on WHO GLASS Surveillance Data: A Retrieval-Augmented Generation Approach for Policy Decision Support
Antimicrobial resistance (AMR) is a growing global crisis projected to cause 10 million deaths per year by 2050. While the WHO Global Antimicrobial Resistance and Use Surveillance System (GLASS) pr...
Md Tanvir Hasan Turja
Does the testing environment matter? Carsickness across on-road, test-track, and driving simulator conditions
Carsickness has gained significant attention with the rise of automated vehicles, prompting extensive research across on-road, test-track, and driving simulator environments to understand its occur...
Georgios Papaioannou, Barys Shyrokau
Deepfake Word Detection by Next-token Prediction using Fine-tuned Whisper
Deepfake speech utterances can be forged by replacing one or more words in a bona fide utterance with semantically different words synthesized by speech generative models. While a dedicated synthet...
Hoan My Tran, Xin Wang, Wanying Ge, Xuechen Liu, Junichi Yamagishi
AHBid: An Adaptable Hierarchical Bidding Framework for Cross-Channel Advertising
In online advertising, the inherent complexity and dynamic nature of advertising environments necessitate the use of auto-bidding services to assist advertisers in bid optimization. This complexity...
Xinxin Yang, Yangyang Tang, Yikun Zhou, Yaolei Liu, Yun Li, Bo Yang
Vectorizing the Trie: Efficient Constrained Decoding for LLM-based Generative Retrieval on Accelerators
Generative retrieval has emerged as a powerful paradigm for LLM-based recommendation. However, industrial recommender systems often benefit from restricting the output space to a constrained subset...
Zhengyang Su, Isay Katsman, Yueqi Wang, Ruining He, Lukasz Heldt, Raghunandan Keshavan, Shao-Chua...