marktechpost4d
Meet KaLM-Embedding: A Series of Multilingual Embedding Models Built on Qwen2-0.5B and Released Under MIT
Multilingual applications and cross-lingual tasks are central to natural language processing (NLP) today, making robust embedding models essential. These models underpin systems like ...
marktechpost4d
This AI Paper Explores Quantization Techniques and Their Impact on Mathematical Reasoning in Large Language Models
Mathematical reasoning stands at the backbone of artificial intelligence and is highly important in arithmetic, geometric, and competition-level problems. Recently, LLMs have emerged as very useful ...
marktechpost4d
Evola: An 80B-Parameter Multimodal Protein-Language Model for Decoding Protein Functions via Natural Language Dialogue
Proteins, essential molecular machines evolved over billions of years, perform critical life-sustaining functions encoded in their sequences and revealed through their 3D structures. Decoding their ...
marktechpost5d
AMD Researchers Introduce Agent Laboratory: An Autonomous LLM-based Framework Capable of Completing the Entire Research Process
Scientific research is often constrained by resource limitations and time-intensive processes. Tasks such as hypothesis testing, data analysis, and report writing demand significant effort, leaving ...
marktechpost5d
Researchers from SynthLabs and Stanford Propose Meta Chain-of-Thought (Meta-CoT): An AI Framework for Improving LLM Reasoning
Large Language Models (LLMs) have significantly advanced artificial intelligence, particularly in natural language understanding and generation. However, these models encounter difficulties with ...
marktechpost5d
The Prompt Alchemist: Automated LLM-Tailored Prompt Optimization for Test Case Generation
Owing to the advent of Artificial Intelligence (AI), the software industry has been leveraging Large Language Models (LLMs) for code completion, debugging, and generating test cases. However, LLMs ...
marktechpost5d
This AI Paper Introduces Virgo: A Multimodal Large Language Model for Enhanced Slow-Thinking Reasoning
Artificial intelligence research has steadily advanced toward creating systems capable of complex reasoning. Multimodal large language models (MLLMs) represent a significant development in this ...
marktechpost5d
This AI Paper Introduces Semantic Backpropagation and Gradient Descent: Advanced Methods for Optimizing Language-Based Agentic Systems
Language-based agentic systems represent a breakthrough in artificial intelligence, allowing for the automation of tasks such as question-answering, programming, and advanced problem-solving. These ...
marktechpost5d
TabTreeFormer: Enhancing Synthetic Tabular Data Generation Through Tree-Based Inductive Biases and Dual-Quantization Tokenization
The generation of synthetic tabular data has become increasingly crucial in fields like healthcare and financial services, where privacy concerns often restrict the use of real-world data. While ...
marktechpost5d
From Contradictions to Coherence: Logical Alignment in AI Models
Large Language Models (LLMs) aim to align with human preferences, ensuring reliable and trustworthy decision-making. However, these models acquire biases, logical leaps, and hallucinations, rendering ...
marktechpost5d
Microsoft AI Just Released Phi-4: A Small Language Model Available on Hugging Face Under the MIT License
Microsoft has released Phi-4, a compact and efficient small language model, on Hugging Face under the MIT license. This decision highlights a shift towards transparency and collaboration in the AI ...
marktechpost6d
Researchers from Princeton University Introduce Metadata Conditioning then Cooldown (MeCo) to Simplify and Optimize Language Model Pre-training
The pre-training of language models (LMs) plays a crucial role in enabling their ability to understand and generate text. However, a significant challenge lies in effectively leveraging the diversity ...