LLM-Based Code Generation Faces a Verification Gap LLMs have shown strong performance in programming and are widely adopted in tools […]
Category: Large Language Model
DeepSeek Researchers Open-Sourced a Personal Project named ‘nano-vLLM’: A Lightweight vLLM Implementation Built from Scratch
The DeepSeek Researchers just released a super cool personal project named ‘nano-vLLM‘, a minimalistic and efficient implementation of the vLLM […]
Why Apple’s Critique of AI Reasoning Is Premature
The debate around the reasoning capabilities of Large Reasoning Models (LRMs) has been recently invigorated by two prominent yet conflicting […]
This AI Paper Introduces WINGS: A Dual-Learner Architecture to Prevent Text-Only Forgetting in Multimodal Large Language Models
Multimodal LLMs: Expanding Capabilities Across Text and Vision Expanding large language models (LLMs) to handle multiple modalities, particularly images and […]
Mistral AI Releases Mistral Small 3.2: Enhanced Instruction Following, Reduced Repetition, and Stronger Function Calling for AI Integration
With the frequent release of new large language models (LLMs), there is a persistent quest to minimize repetitive errors, enhance […]
Meta AI Researchers Introduced a Scalable Byte-Level Autoregressive U-Net Model That Outperforms Token-Based Transformers Across Language Modeling Benchmarks
Language modeling plays a foundational role in natural language processing, enabling machines to predict and generate text that resembles human […]
MiniMax AI Releases MiniMax-M1: A 456B Parameter Hybrid Model for Long-Context and Reinforcement Learning RL Tasks
The Challenge of Long-Context Reasoning in AI Models Large reasoning models are not only designed to understand language but are […]
ReVisual-R1: An Open-Source 7B Multimodal Large Language Model (MLLMs) that Achieves Long, Accurate and Thoughtful Reasoning
The Challenge of Multimodal Reasoning Recent breakthroughs in text-based language models, such as DeepSeek-R1, have demonstrated that RL can aid […]
EPFL Researchers Introduce MEMOIR: A Scalable Framework for Lifelong Model Editing in LLMs
The Challenge of Updating LLM Knowledge LLMs have shown outstanding performance for various tasks through extensive pre-training on vast datasets. […]
Internal Coherence Maximization (ICM): A Label-Free, Unsupervised Training Framework for LLMs
Post-training methods for pre-trained language models (LMs) depend on human supervision through demonstrations or preference feedback to specify desired behaviors. […]