The first dynamic algorithms for matrix rank and related objects achieve update times scaling with rank r, specifically Õ(r^1.405) per entry update and Õ(r^1.528 + z) per column update, extending to dynamic maximum matching.
Fully Dynamic Maximal Independent Set with Polylogarithmic Update Time , booktitle =
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An algorithm for online Steiner forest achieves constant competitiveness with amortized O(log n) recourse.
A deterministic semi-streaming algorithm achieves an O(Δ)-coloring in O(√log Δ) passes, the first with linear palette size and sublogarithmic passes.
MultiLogBench shows that LLM performance on automated logging varies substantially across programming languages, demonstrating that single-language evidence is insufficient for general claims about model behavior or tool design.
Small-scale programs exhibit notable compile-time and run-time configurability that grows over time and correlates with size, supporting the value of reducing variability for simpler software.
UFPR-VeSV is a new real-world dataset for fine-grained vehicle classification and automatic license plate recognition collected from Brazilian police cameras, with benchmarks demonstrating its difficulty and the value of joint task use.
citing papers explorer
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Dynamic Rank, Basis, and Matching
The first dynamic algorithms for matrix rank and related objects achieve update times scaling with rank r, specifically Õ(r^1.405) per entry update and Õ(r^1.528 + z) per column update, extending to dynamic maximum matching.
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Online Steiner Forest with Recourse
An algorithm for online Steiner forest achieves constant competitiveness with amortized O(log n) recourse.
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Faster Deterministic Streaming Vertex Coloring
A deterministic semi-streaming algorithm achieves an O(Δ)-coloring in O(√log Δ) passes, the first with linear palette size and sublogarithmic passes.
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Single-Language Evidence Is Insufficient for Automated Logging: A Multilingual Benchmark and Empirical Study with LLMs
MultiLogBench shows that LLM performance on automated logging varies substantially across programming languages, demonstrating that single-language evidence is insufficient for general claims about model behavior or tool design.
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Small Yet Configurable: Unveiling Null Variability in Software
Small-scale programs exhibit notable compile-time and run-time configurability that grows over time and correlates with size, supporting the value of reducing variability for simpler software.
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Toward Unified Fine-Grained Vehicle Classification and Automatic License Plate Recognition
UFPR-VeSV is a new real-world dataset for fine-grained vehicle classification and automatic license plate recognition collected from Brazilian police cameras, with benchmarks demonstrating its difficulty and the value of joint task use.