🌐 Entity

Reasoning model

Language models designed for reasoning tasks

📊 Rating

8 news mentions · 👍 0 likes · 👎 0 dislikes

📌 Topics

Artificial Intelligence (8)
Machine Learning (6)
Technology (2)
Computer Science (1)
Cybersecurity (1)
Resource Management (1)
Computational Efficiency (1)
Reasoning Models (1)
Technology Research (1)
Algorithm Research (1)
Model Efficiency (1)

🏷️ Keywords

arXiv (7) · Large Reasoning Models (7) · Reinforcement Learning (3) · Chain of Thought (2) · Free()LM (1) · Reasoning Models (1) · Large Language Models (1) · Test-time Compute (1) · Malloc-only (1) · Artificial Intelligence (1) · Memory Management (1) · RECUR attack (1) · Resource exhaustion (1) · Adversarial AI (1) · Recursive entropy (1) · LRM (1) · AI Redundancy (1) · Inference Latency (1) · Artificial Intelligence Research (1) · Parallel Thinking (1)

📖 Key Information

A reasoning model, also known as reasoning language models (RLMs) or large reasoning models (LRMs), is a type of large language model (LLM) that has been specifically trained to solve complex tasks requiring multiple steps of logical reasoning. These models demonstrate superior performance on logic, mathematics, and programming tasks compared to standard LLMs. They possess the ability to revisit and revise earlier reasoning steps and utilize additional computation during inference as a method to scale performance, complementing traditional scaling approaches based on training data size, model parameters, and training compute.

📰 Related News (8)

🇺🇸 Free(): Learning to Forget in Malloc-Only Reasoning Models (2026-02-10)
arXiv:2602.08030v1 Announce Type: new Abstract: Reasoning models enhance problem-solving by scaling test-time compute, yet they face a critical parad...
🇺🇸 RECUR: Resource Exhaustion Attack via Recursive-Entropy Guided Counterfactual Utilization and Reflection (2026-02-10)
arXiv:2602.08214v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) employ reasoning to address complex tasks. Such explicit reasoning requ...
🇺🇸 Does Your Reasoning Model Implicitly Know When to Stop Thinking? (2026-02-10)
arXiv:2602.08354v1 Announce Type: new Abstract: Recent advancements in large reasoning models (LRMs) have greatly improved their capabilities on comp...
🇺🇸 OPE: Overcoming Information Saturation in Parallel Thinking via Outline-Guided Path Exploration (2026-02-10)
arXiv:2602.08344v1 Announce Type: new Abstract: Parallel thinking has emerged as a new paradigm for large reasoning models (LRMs) in tackling complex...
🇺🇸 InftyThink+: Effective and Efficient Infinite-Horizon Reasoning via Reinforcement Learning (2026-02-09)
arXiv:2602.06960v1 Announce Type: cross Abstract: Large reasoning models achieve strong performance by scaling inference-time chain-of-thought, but t...
🇺🇸 Difficulty-Estimated Policy Optimization (2026-02-09)
arXiv:2602.06375v1 Announce Type: new Abstract: Recent advancements in Large Reasoning Models (LRMs), exemplified by DeepSeek-R1, have underscored th...
🇺🇸 Exposing Weaknesses of Large Reasoning Models through Graph Algorithm Problems (2026-02-09)
arXiv:2602.06319v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) have advanced rapidly; however, existing benchmarks in mathematics, cod...
🇺🇸 Steering Large Reasoning Models towards Concise Reasoning via Flow Matching (2026-02-07)
arXiv:2602.05539v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) excel at complex reasoning tasks, but their efficiency is often hampe...

🔗 Entity Intersection Graph

People and organizations frequently mentioned alongside Reasoning model:

🌐 Reinforcement learning (3 shared articles)
🌐 Chain of thought (2 shared articles)
🌐 LRM (1 shared articles)
🌐 Vector field (1 shared articles)
🌐 Resource exhaustion attack (1 shared articles)
🌐 Adversarial machine learning (1 shared articles)
🌐 Large language model (1 shared articles)
🌐 Artificial intelligence (1 shared articles)
🌐 Machine learning (1 shared articles)

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