Noticias
Can We Improve Llama 3’s Reasoning Through Post-Training Alone? ASTRO Shows +16% to +20% Benchmark Gains
Improving the reasoning capabilities of large language models (LLMs) without architectural changes is a core...
Can Vision Language Models Infer Human Gaze Direction? A Controlled Study
arXiv:2506.05412v1 Announce Type: cross Abstract: Gaze-referential inference–the ability to infer what others are looking at–is...
Can structural correspondences ground real world representational content in Large Language Models?
arXiv:2506.16370v1 Announce Type: new Abstract: Large Language Models (LLMs) such as GPT-4 produce compelling responses...
Can Prompting LLMs Unlock Hate Speech Detection across Languages? A Zero-shot and Few-shot Study
arXiv:2505.06149v1 Announce Type: new Abstract: Despite growing interest in automated hate speech detection, most existing...
Can nuclear power really fuel the rise of AI?
In the AI arms race, all the major players say they want to go nuclear. ...
Can Multimodal Foundation Models Understand Schematic Diagrams? An Empirical Study on Information-Seeking QA over Scientific Papers
arXiv:2507.10787v1 Announce Type: new Abstract: This paper introduces MISS-QA, the first benchmark specifically designed to...
Can LLMs Really Judge with Reasoning? Microsoft and Tsinghua Researchers Introduce Reward Reasoning Models to Dynamically Scale Test-Time Compute for Better Alignment
Reinforcement learning (RL) has emerged as a fundamental approach in LLM post-training, utilizing supervision signals...
Can LLMs Generate Reliable Test Case Generators? A Study on Competition-Level Programming Problems
arXiv:2506.06821v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in code...
Can crowdsourced fact-checking curb misinformation on social media?
In a 2019 speech at Georgetown University, Mark Zuckerberg famously declared that he didn’t want...
Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding
arXiv:2505.03788v1 Announce Type: new Abstract: We introduce a novel approach for calibrating uncertainty quantification (UQ)...
ByteDance Researchers Introduce DetailFlow: A 1D Coarse-to-Fine Autoregressive Framework for Faster, Token-Efficient Image Generation
Autoregressive image generation has been shaped by advances in sequential modeling, originally seen in natural...
By putting AI into everything, Google wants to make it invisible
If you want to know where AI is headed, this year’s Google I/O has you...
