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639 papers
This work introduces Risa (Routing-Informed Steering and Arbitration): within trajectories, routing encourages diverse exploration and controlled convergence during patch commitment; across separately sampled trajectories, agreement at informative patch positions selects a final candidate.
DPIAgent is proposed, a structured agentic framework built on three principles, Divide, Protocol, Isolate (DPI), that mitigates compound-objective ambiguity and goal drift, and shows that architectural structure and backbone capability are complementary axes rather than substitutes, demonstrating DPI's generalizability across model classes.
SWE Refactor Bench is introduced, a benchmark comprising 20 whole-repository migrations, covering 4 kinds of technical debt, and SWE Refactor Bench is positioned as a rigorous testbed for developing coding agents for reliable whole-repository migrations.
Neuro-formal verification is introduced, which harnesses that automation for developers of mainstream programming languages and returns a Dafny proof of correctness or of a bug on 57% of the entries at 92% precision, and a CBMC counterexample for 63% of the buggy programs at 90% precision.
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The first complete description of SweepLSD is given, a line segment detector that reads the image exactly once and emits each segment within a few rows of its last pixel passing the scan line, with the tightest frame-time distribution and the best per-segment direction accuracy of the four detectors.
The ezSRT test is capable of producing reliable SRT estimates in 6 min that are sensitive to different experimental conditions and listener groups and that result in different SiN performance levels when later tested in a fixed SNR configuration, and using the ezSRT test as part of the new i-RRT protocol to determine SNRs targeting specific intelligibility levels.
This study aims to analyze the effect of independent commissioners, audit committees, and institutional ownership on stock returns of companies listed on the Indonesia Stock Exchange during the 2021–2024 period. The background of this research is based on the importance of implementing good corporate governance in enhancing investor confidence and capital market performance, particularly in the context of post-pandemic market dynamics characterized by economic uncertainty and stock price volatility. This study employs a quantitative approach to examine the causal relationship between independent and dependent variables in an objective, systematic, and measurable manner. The data used in this study are secondary data obtained from companies’ financial statements and other relevant officially published sources. The analytical method applied is panel data regression using EViews software, preceded by model selection tests and classical assumption tests to ensure the validity and reliability of the results. The findings indicate that, partially, independent commissioners and institutional ownership do not have a significant effect on stock returns. In contrast, the audit committee shows a significant effect, indicating that the effectiveness of the monitoring function is able to enhance investor confidence in the company.These findings suggest that not all corporate governance mechanisms have a direct impact on stock return movements in the capital market. Therefore, it can be concluded that the audit committee is a key factor influencing stock returns, while independent commissioners and institutional ownership have not demonstrated a significant effect. This study is expected to contribute to companies in improving governance effectiveness and to serve as a reference for investors in evaluating the quality of internal control. Furthermore, future research is recommended to extend the observation period, include additional financial control variables such as ROA, ROE, and dividend policy, and consider external factors such as macroeconomic conditions to obtain more comprehensive and generalizable results.
This study suggests early remodeling of the stromal microenvironment and possible differences in the immune makeup with increased myeloid numbers and activation in progressors in patients who progress.
The implementation results indicate that HadiRin can support a more measurable attendance process and improve attendance accountability through the combination of location verification and selfie capture and further development can focus on strengthening system security through location anti-spoofing mechanisms and liveness detection.
An open-source, human-verified workflow using large language models can accelerate electronic health record abstraction while improving accuracy and supports broader adoption of transparent artificial intelligence methods in clinical research.
This work introduces a static, decompiler-driven pipeline built on top of Ghidra that augments decompiled functions with binary-derived evidence including recovered stack regions, callgraph context, and p-code-derived features and presents the real-world evaluation as a diagnostic stress test rather than evidence of a deployable detector.
It is suggested that process-oriented metrics, particularly those related to code testing and development history, capture defect patterns more effectively per feature than static code structure metrics, offering practical guidance for software quality assurance.
In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
MIT students designed, built, and tested a jet engine with AI copilots, assessing AI’s usefulness in developing high-performance aerospace systems.
Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.
A USAF cadet and a Lincoln Laboratory researcher found AI chatbots can help nontechnical service members produce viable software applications for their unique problems.
Our latest voice model has improved precision and lower latency to make voice interactions more fluid, natural and precise.
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