Building an AI Research Agent for Essay Writing
In this tutorial, we will build an advanced AI-powered research agent that can write essays on given topics. This agent follows a structured workflow: Planning: Generates an outline for the…
Are Autoregressive LLMs Really Doomed? A Commentary on Yann LeCun’s Recent Keynote at AI Action Summit
Yann LeCun, Chief AI Scientist at Meta and one of the pioneers of modern AI, recently argued that autoregressive Large Language Models (LLMs) are fundamentally flawed. According to him, the…
This AI Paper Introduces CodeSteer: Symbolic-Augmented Language Models via Code/Text Guidance
Large language models (LLMs) struggle with precise computations, symbolic manipulations, and algorithmic tasks, often requiring structured problem-solving approaches. While language models demonstrate strengths in semantic understanding and common sense reasoning,…
NuminaMath 1.5: Second Iteration of NuminaMath Advancing AI-Powered Mathematical Problem Solving with Enhanced Competition-Level Datasets, Verified Metadata, and Improved Reasoning Capabilities
Mathematical reasoning remains one of the most complex challenges in AI. While AI has advanced in NLP and pattern recognition, its ability to solve complex mathematical problems with human-like logic…
Vintix: Scaling In-Context Reinforcement Learning for Generalist AI Agents
Developing AI systems that learn from their surroundings during execution involves creating models that adapt dynamically based on new information. In-Context Reinforcement Learning (ICRL) follows this approach by allowing AI…
Advancing Scalable Text-to-Speech Synthesis: Llasa’s Transformer-Based Framework for Improved Speech Quality and Emotional Expressiveness
Recent advancements in LLMs, such as the GPT series and emerging “o1” models, highlight the benefits of scaling training and inference-time computing. While scaling during training—by increasing model size and…
Shanghai AI Lab Releases OREAL-7B and OREAL-32B: Advancing Mathematical Reasoning with Outcome Reward-Based Reinforcement Learning
Mathematical reasoning remains a difficult area for artificial intelligence (AI) due to the complexity of problem-solving and the need for structured, logical thinking. While large language models (LLMs) have made…
This AI Paper Explores Long Chain-of-Thought Reasoning: Enhancing Large Language Models with Reinforcement Learning and Supervised Fine-Tuning
Large language models (LLMs) have demonstrated proficiency in solving complex problems across mathematics, scientific research, and software engineering. Chain-of-thought (CoT) prompting is pivotal in guiding models through intermediate reasoning steps…
LLMDet: How Large Language Models Enhance Open-Vocabulary Object Detection
Open-vocabulary object detection (OVD) aims to detect arbitrary objects with user-provided text labels. Although recent progress has enhanced zero-shot detection ability, current techniques handicap themselves with three important challenges. They…
Zyphra Introduces the Beta Release of Zonos: A Highly Expressive TTS Model with High Fidelity Voice Cloning
Text-to-speech (TTS) technology has made significant strides in recent years, but challenges remain in creating natural, expressive, and high-fidelity speech synthesis. Many TTS systems struggle to replicate the nuances of…
Pop-Tarts With Protein?! 3 New Flavors Are Dropping Soon
JuicyTalk
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A Weekend of Reckonings: Liverpool–United Tops a Defining Premier League Round
- October 16, 2025
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Meet the founder making breast cancer awareness simple and accessible
- October 16, 2025
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