Mathematical reasoning remains one of the most complex challenges in AI. While AI has advanced in NLP and pattern recognition, […]
Category: Applications
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 […]
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) […]
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 […]
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 […]
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. […]
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 […]
Efficient Alignment of Large Language Models Using Token-Level Reward Guidance with GenARM
Large language models (LLMs) must align with human preferences like helpfulness and harmlessness, but traditional alignment methods require costly retraining […]
Tutorial to Fine-Tuning Mistral 7B with QLoRA Using Axolotl for Efficient LLM Training
In this tutorial, we demonstrate the workflow for fine-tuning Mistral 7B using QLoRA with Axolotl, showing how to manage limited […]
Adaptive Inference Budget Management in Large Language Models through Constrained Policy Optimization
Large Language Models (LLMs) have demonstrated remarkable capabilities in complex reasoning tasks, particularly in mathematical problem-solving and coding applications. Research […]