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🔍 daniela opocenska 📂 Computer Science
Showing 469 results for "daniela opocenska" in Computer Science
Computer Science Preprint PDF DOI

Predicting Upcoming Stuttering Events from Three-Second Audio: Stratified Evaluation Reveals Severity-Selective Precursors, and the Model Deploys Fully On-Device

Nazar Kozak · 2026

Audio-based stuttering systems to date have been trained for detection -- what disfluency is present now -- leaving prediction, the capability needed for closed-loop intervention, unstudied at deploya…

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Computer Science Preprint PDF DOI

StreamGuard: Exploring a 5G Architecture for Efficient, Quality of Experience-Aware Video Conferencing

Xuyang Cao, Oliver Michel, Kyle Jamieson · 2026

Video conferencing over 5G is increasingly prevalent, yet its Quality of Experience (QoE) often degrades under limited radio resources. This has two causes: 5G networks must serve many users, while in…

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Computer Science Preprint PDF DOI

Praxy Voice: Voice-Prompt Recovery + BUPS for Commercial-Class Indic TTS from a Frozen Non-Indic Base at Zero Commercial-Training-Data Cost

Venkata Pushpak Teja Menta · 2026

Commercial TTS systems produce near-native Indic audio, but the best open-source bases (Chatterbox, Indic Parler-TTS, IndicF5) trail them on measured phonological dimensions, and the most widely adopt…

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Computer Science Preprint PDF DOI

ZFLean: a framework for set-level mathematics in Lean

Vincent Trelat · 2026

We present ZFLean, a Lean 4 library for doing core mathematics inside a model of ZFC with the ergonomics expected of typed Mathlib developments. Building on Mathlib's ZFC model, we contribute a relati…

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Computer Science Preprint PDF DOI

Closing the Loop: A Software Framework for AI to Support Business Decision Making

Jeffrey Wong, Antoine Creux · 2026

Create an idea, prototype it, evaluate if users like it, then learn. It is the circle of business. If AI can operate in all parts of the circle, it will enable rapid iteration and learning speeds for …

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Computer Science Preprint PDF DOI

HeadRouter: Dynamic Head-Weight Routing for Task-Adaptive Audio Token Pruning in Large Audio Language Models

Peize He, Yaodi Luo, Xiaoqian Liu, Xuyang Liu, Jiahang Deng, Yaosong Du, Bangyu Li, Xiyan Gui, Yuxuan Chen, Linfeng Zhang · 2026

Recent large audio language models (LALMs) demonstrate remarkable capabilities in processing extended multi-modal sequences, yet incur high inference costs. Token compression is an effective method th…

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Computer Science Preprint PDF DOI

AutoINV: Automated Invariant Generation Framework for Formal Verification on High-Level Synthesis Designs

Xiaofeng Zhou, Linfeng Du, Guangyu Hu, Sharad Sinha, Hongce Zhang, Wei Zhang · 2026

High-level synthesis (HLS) transforms an algorithmic description of hardware from a higher abstraction (e.g., C/C++) into a register-transfer level (RTL) design, offering reduced development time and …

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Computer Science Preprint PDF DOI

DebugRepair: Enhancing LLM-Based Automated Program Repair via Self-Directed Debugging

Linhao Wu, Yifei Pei, Zhen Yang, Kainan Li, Zhonghang Lu, Hao Tan, Xiran Lyu, Jia Li, Yizhou Chen, Pengyu Xue, Kunwu Zheng, Dan Hao · 2026

Automated Program Repair (APR) has benefited from the code understanding and generation capabilities of Large Language Models (LLMs). Existing feedback-based APR methods iteratively refine candidate p…

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Computer Science Preprint PDF DOI

Last-Iterate Guarantees for Learning in Co-coercive Games

Siddharth Chandak, Ramanan Tamizholi, Nicholas Bambos · 2026

We establish finite-time last-iterate guarantees for vanilla stochastic gradient descent in co-coercive games under noisy feedback. This is a broad class of games that is more general than strongly mo…

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Computer Science Preprint PDF DOI

WebCompass: Towards Multimodal Web Coding Evaluation for Code Language Models

Xinping Lei, Xinyu Che, Junqi Xiong, Chenchen Zhang, Yukai Huang, Chenyu Zhou, Haoyang Huang, Minghao Liu, Letian Zhu, Hongyi Ye, Jinhua Hao, Ken Deng, Zizheng Zhan, Han Li, Dailin Li, Yifan Yao, Ming Sun, Zhaoxiang Zhang, Jiaheng Liu · 2026

Large language models are rapidly evolving into interactive coding agents capable of end-to-end web coding, yet existing benchmarks evaluate only narrow slices of this capability, typically text-condi…

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Computer Science Preprint PDF DOI

WISV: Wireless-Informed Semantic Verification for Distributed Speculative Decoding in Device-Edge LLM Inference

Zixuan Liu, Zhiyong Chen, Nan Xue, Shengkang Chen, Jiangchao Yao, Meixia Tao, Wenjun Zhang · 2026

While distributed device-edge speculative decoding enhances resource utilization across heterogeneous nodes, its performance is often bottlenecked by conventional token-level verification strategies. …

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Computer Science Preprint PDF DOI

From Transfer to Collaboration: A Federated Framework for Cross-Market Sequential Recommendation

Jundong Chen, Honglei Zhang, Xiangmou Qu, Haoxuan Li, Han Yu, Yidong Li · 2026

Cross-market recommendation (CMR) aims to enhance recommendation performance across multiple markets. Due to its inherent characteristics, i.e., data isolation, non-overlapping users, and market heter…

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Computer Science Preprint PDF DOI

Vanilla Object Orientation (VOO): A Value-Semantics Approach to Classes in Tcl

Alan Araujo · 2026

I present Vanilla Object Orientation (VOO), a framework that composes classes from Tcl's native data structures -- lists and dictionaries -- rather than introducing additional framework infrastructure…

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Computer Science Preprint PDF DOI

GEMM-GS: Accelerating 3D Gaussian Splatting on Tensor Cores with GEMM-Compatible Blending

Haomin Li, Bowen Zhu, Fangxin Liu, Zongwu Wang, Xinran Liang, Li Jiang, Haibing Guan · 2026

Neural Radiance Fields (NeRF) enables 3D scene reconstruction from several 2D images but incurs high rendering latency via its point-sampling design. 3D Gaussian Splatting (3DGS) improves on NeRF with…

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Computer Science Preprint PDF DOI

TestDecision: Sequential Test Suite Generation via Greedy Optimization and Reinforcement Learning

Guoqing Wang, Chengran Yang, Xiaoxuan Zhou, Zeyu Sun, Bo Wang, David Lo, Dan Hao · 2026

With the rapid evolution of LLMs, automated software testing is witnessing a paradigm shift. While proprietary models like GPT-4o demonstrate impressive capabilities, their high deployment costs and d…

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Computer Science Preprint PDF DOI

Do We Still Need GraphRAG? Benchmarking RAG and GraphRAG for Agentic Search Systems

Dongzhe Fan, Zheyi Xue, Siyuan Liu, Qiaoyu Tan · 2026

Retrieval-augmented generation (RAG) and its graph-based extensions (GraphRAG) are effective paradigms for improving large language model (LLM) reasoning by grounding generation in external knowledge.…

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Computer Science Preprint PDF DOI

Finding Memory Leaks in C/C++ Programs via Neuro-Symbolic Augmented Static Analysis

Huihui Huang, Jieke Shi, Bo Wang, Zhou Yang, David Lo · 2026

Memory leaks remain prevalent in real-world C/C++ software. Static analyzers such as CodeQL provide scalable program analysis but frequently miss such bugs because they cannot recognize project-specif…

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Computer Science Preprint PDF DOI

VILLA: Versatile Information Retrieval From Scientific Literature Using Large LAnguage Models

Blessy Antony, Amartya Dutta, Sneha Aggarwal, Vasu Gatne, Ozan Gokdemir, Samantha Grimes, Adam Lauring, Brian R. Wasik, Anuj Karpatne, T. M. Murali · 2026

The lack of high-quality ground truth datasets to train machine learning (ML) models impedes the potential of artificial intelligence (AI) for science research. Scientific information extraction (SIE)…

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Computer Science Preprint PDF DOI

A Pipelined Collaborative Speculative Decoding Framework for Efficient Edge-Cloud LLM Inference

Yida Zhang, Zhiyong Gao, Shuaibing Yue, Jie Li, Rui Wang · 2026

Recent advancements and widespread adoption of Large Language Models (LLMs) in both industry and academia have catalyzed significant demand for LLM serving. However, traditional cloud services incur h…

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Computer Science Preprint PDF DOI

TDAD: Test-Driven Agentic Development - Reducing Code Regressions in AI Coding Agents via Graph-Based Impact Analysis

Pepe Alonso, Sergio Yovine, Victor A. Braberman · 2026

AI coding agents can resolve real-world software issues, yet they frequently introduce regressions -- breaking tests that previously passed. Current benchmarks focus almost exclusively on resolution r…

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