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Research & Development
Enhancing Code Review with Fine-Tuned Language Models: A C# Case Study
TLDR: This study explores fine-tuning multilingual language models (CodeReviewer, CodeLlama-7B, DeepSeek-R1-Distill) on C# code for automated code review tasks like quality estimation, comment generation,...
Research & Development
AI-Powered Tabular Data Synthesis: Speed and Accuracy Combined
TLDR: SPADA is a new framework for generating high-quality synthetic tabular data. It uses large language models (LLMs) to identify sparse dependencies between data...
Research & Development
Smooth Reading: Empowering Recurrent LLMs for Long Documents
TLDR: The research paper introduces 'Smooth Reading,' a novel inference method that significantly improves Recurrent Large Language Models (LLMs) performance on long-context tasks, making...
Research & Development
Assessing Voice Understanding in AI: Introducing the Speech Intelligence Quotient
TLDR: SpeechIQ is a new evaluation framework for voice understanding large language models (LLMVoice) that goes beyond traditional metrics like Word Error Rate (WER)....
Research & Development
Enhancing Spoken Language Correction with Automated Data Generation
TLDR: This research introduces an automated pipeline to generate synthetic audio-text data with grammatical errors and disfluencies, addressing the scarcity of spoken grammatical error...
Research & Development
Uncovering Hidden Risks: A New Benchmark for LLM Code Interpreter Security
TLDR: The CIRCLE benchmark evaluates the security of LLM code interpreters against resource exhaustion attacks (CPU, memory, disk). It uses both direct and indirect...