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This AI Paper Introduces MathCoder-VL and FigCodifier: Advancing Multimodal Mathematical Reasoning with Vision-to-Code Alignment
Multimodal mathematical reasoning enables machines to solve problems involving textual information and visual components like...
This AI Paper Introduces LLaDA-V: A Purely Diffusion-Based Multimodal Large Language Model for Visual Instruction Tuning and Multimodal Reasoning
Multimodal large language models (MLLMs) are designed to process and generate content across various modalities...
This AI Paper Introduces Group Think: A Token-Level Multi-Agent Reasoning Paradigm for Faster and Collaborative LLM Inference
A prominent area of exploration involves enabling large language models (LLMs) to function collaboratively. Multi-agent...
This AI Paper Introduces GRIT: A Method for Teaching MLLMs to Reason with Images by Interleaving Text and Visual Grounding
The core idea of Multimodal Large Language Models (MLLMs) is to create models that can...
This AI Paper Introduces Differentiable MCMC Layers: A New AI Framework for Learning with Inexact Combinatorial Solvers in Neural Networks
Neural networks have long been powerful tools for handling complex data-driven tasks. Still, they often...
This AI Paper from Microsoft Introduces WINA: A Training-Free Sparse Activation Framework for Efficient Large Language Model Inference
Large language models (LLMs), with billions of parameters, power many AI-driven services across industries. However...
This AI paper from DeepSeek-AI Explores How DeepSeek-V3 Delivers High-Performance Language Modeling by Minimizing Hardware Overhead and Maximizing Computational Efficiency
The growth in developing and deploying large language models (LLMs) is closely tied to architectural...
Thinking with Many Minds: Using Large Language Models for Multi-Perspective Problem-Solving
arXiv:2501.02348v2 Announce Type: replace Abstract: Complex problem-solving requires cognitive flexibility–the capacity to entertain multiple perspectives...
Thinking Machines Launches Tinker: A Low-Level Training API that Abstracts Distributed LLM Fine-Tuning without Hiding the Knobs
Thinking Machines has released Tinker, a Python API that lets researchers and engineers write training...
Theorem-of-Thought: A Multi-Agent Framework for Abductive, Deductive, and Inductive Reasoning in Language Models
arXiv:2506.07106v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong performance across natural...
The World According to LLMs: How Geographic Origin Influences LLMs’ Entity Deduction Capabilities
arXiv:2508.05525v1 Announce Type: new Abstract: Large Language Models (LLMs) have been extensively tuned to mitigate...
The walled garden cracks: Nadella bets Microsoft’s Copilots—and Azure’s next act—on A2A/MCP interoperability
Microsoft CEO Satya Nadella’s endorsement of Google DeepMind‘s A2A open protocol and Anthropic’s MCP is...
