Similar papers
Evaluating the Performance of Large Language Models on GAOKAO Benchmark
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.
· arXiv.org · 216 citations
· ⚡17
Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
Kyra Wilson, Aylin Caliskan
· AAAI/ACM Conference on AI, E... · 131 citations
· ⚡8
Ultralytics YOLO Evolution: An Overview of YOLO26, YOLO11, YOLOv8 and YOLOv5 Object Detectors for Computer Vision and Pattern Recognition
This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 through YOLO27, and examines detection, segmentation, depth, classification, pose, oriented detection, tracking, export, quantization, and deplo...
Ranjan Sapkota, Manoj Karkee
· arXiv.org · 112 citations
· ⚡10
#artificial intelligence
Jun 2024
BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models
A novel threat is unveiled in which attackers steer the RAG system's response by injecting malicious passages into its knowledge base, enabling the attacker to steer the response without altering the user input or modifying the RAG weights.
Jiaqi Xue, Meng Zheng, Yebowen Hu et al.
· arXiv.org · 109 citations
· ⚡8
#artificial intelligence
Aug 2024
The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Models
This work revisits schema linking when using the latest generation of large language models (LLMs) and finds empirically that newer models are adept at utilizing relevant schema elements during generation even in the presence of large numbers of irrelevant ones.
Karime Maamari, Fadhil Abubaker, Daniel Jaroslawicz et al.
· arXiv.org · 109 citations
· ⚡19
#artificial intelligence
Feb 2025
PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection
Empirically, PRISM reduces the end-to-end time for data selection and model tuning to just 30% of conventional pipelines, and achieves this efficiency while simultaneously enhancing performance, surpassing models fine-tuned on the full dataset across eight multimodal and three language understanding benchmarks.
Jinhe Bi, Yifan Wang, Danqi Yan et al.
· arXiv.org · 73 citations
· ⚡4
Related blog posts
Google DeepMind Blog
· deepmind.google
Sep 30, 2026
Gemini 4 Argon: our next era of frontier intelligence
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
MIT News · Artificial Intelligence
· news.mit.edu
Sep 30, 2026
MIT Transit Lab to develop an AI platform for public transit agencies
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
Hugging Face Blog
· huggingface.co
Sep 30, 2026
Open TTS Leaderboard: Scalable Evaluation for Multilingual Text-to-Speech and Voice Cloning
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
MIT News · Artificial Intelligence
· news.mit.edu
Sep 29, 2026
Who we become when we talk to machines
Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.