🔍 Cómo monitoreamos agentes de codificación interna por desalineación
Cómo OpenAI usa monitoreo de cadena de pensamiento para estudiar la desalineación en agentes de cod
openai.com/index/how-we-monitor-int...
#AISafety #ChainOfThought #AIAlignment #RoxsRoss
Tek cümle eklemeniz yeter: "Adım adım düşün." ✨ (8/8)
#adımadımdüşün #düşüncezinciri #chainofthought #yapayzeka #ai
Just saw TensorRT Edge‑LLM crush chain‑of‑thought reasoning on‑device, unlocking Physical AI for autonomous cars. Imagine real‑time MATH500 puzzles solved in the car! Dive in to see how edge LLMs are changing the game. #TensorRT #EdgeLLM #ChainOfThought
🔗 aidailypost.com/news/tensorr...
Chain of Thought CoT AI #chainofthought #ai #aihype #ki #künstlicheintelligenz #skynet #terminator
Can we trust an AI's "Chain of Thought" if the model can secretly edit its own reasoning? 🧠
#AISafety #LLM #MachineLearning #AIResearch #ChainOfThought #TechEthics
Source: arxiv.org/pdf/2603.05706
What Are AI Reasoning Models?
awesomeagents.ai/guides/what-are-ai-reaso...
#AiReasoning #ChainOfThought #Llms
#EricJang argues that #AImodels can now genuinely think and code. Using #ClaudeCode, he demonstrates #automatedresearch workflows, traces reasoning’s evolution from #ChainofThought to #DeepSeekR1, and predicts massive demand for inference compute. #Codingagents will fundamentally transform…
DeepSeek-R1 and QwQ-3 show off opposite personalities that boost reasoning—think chain-of-thought meets a split-brain vibe. Curious how personality diversity sharpens AI? Dive in! #DeepSeekR1 #QwQ3 #ChainOfThought
🔗 aidailypost.com/news/deepsee...
“Reasoning models” are teaching AI to think. Instead of one shot answers, these systems break problems into steps, explore multiple paths, & then commit to the best solution.
Full breakdown:
techglimmer.io/what-is-ai-t...
#AI #ReasoningModels #GenAI #ChainOfThought #AIResearch
Chain-of-Thought prompting shows diminishing returns in modern LLMs. Non-reasoning models show mixed results—improved averages but increased variability. However CoT is still relevant for learning and transparency/control. #AIprompting #ChainOfThought #Wharton
Answers are cheap. Understanding the AI’s reasoning Priceless.
#AITrust #ChainOfThought #LLM #AIGovernance #DigitalTransformation
openai.com/index/evalua...
Can We Trust AI Explanations? Evidence of Systematic Underreporting in Chain-of-Thought Reasoning
Deep Pankajbhai Mehta
Paper
Details
#AIExplainability #ChainOfThought #ResearchTransparency
给了机关枪，你却非要耍大刀：2025 年末，程序员 All in AI 的生存启示录 本文永久链接 – tonybai.com/2025/12/09/programmer-al...
#技术志 #2025年末 #AgenticTools #AI #AI原生工作流 #AllinAI #ChainofThought #ChatGPT #ClaudeCode #ContextInjection #Copilot
Origin | Interest | Match
If you want to spend time on AI you can best spend it on lectures like this. No hype, just science, but in this case also very practical.
youtu.be/k1njvbBmfsw?...
#AI #Stanford #RAG #Prompting #Chainofthought #agenticAI
"모델 크기는 더 이상 절대 규칙이 아닙니다."
Test-Time Compute & Scaling Laws 완벽 가이드! 7B+TTC vs 140B 모델 FLOPs 기준 성능. Chinchilla 함정: 훈련 최적≠추론 최적. Sequential vs Parallel Scaling 비교, 자기수정 능력 부재 분석. Compute-Optimal 난이도별 할당. 수학 성능 6배 향상, IOI 금메달 달성! 미래 아키텍처 최적화까지!
#ChainofThought
doyouknow.kr/652/test-tim...
추론형 AI 완벽 가이드! o1 수학 83.3%, 코딩 89%, 의료 진단 87.7% 정확도. System 1 vs System 2 사고 구현. Chain-of-Thought 진화: Few-shot → Zero-shot → o1 내부 추론. DeepSeek-R1: o1 성능 유지, 비용 1/27! 투명한 추론 vs 숨겨진 추론 비교, 미래 Multi-round Thinking까지!
#ChainofThought #CoT #DeepSeekR1 #LLM #o1
doyouknow.kr/644/reasonin...
LLM이 추가 학습 없이 똑똑해지는 비밀! In-Context Learning 완벽 분석. Zero-shot, Few-shot, Chain-of-Thought(CoT), Tree-of-Thought(ToT), Self-Consistency 기법별 성능 비교. GSM8K 수학 17%→78% 향상! "Let's think step by step" 한 줄의 마법, ICL 원리와 실전 활용 가이드.
#AI추론 #ChainofThought #CoT #FewshotLearning
doyouknow.kr/593/in-conte...
New study maps how LLMs reason step‑by‑step and spots where they stumble—think moral dilemmas, autopilot decisions, and benchmark puzzles. See the detailed traces and what they mean for future AI. #ChainOfThought #ReasoningTraces #AIBenchmark
🔗 aidailypost.com/news/study-m...
Check out the full paper with Omar Montasser & John Lafferty!
* Paper: arxiv.org/pdf/2505.15927
* Blog: awni.xyz/cot-info/
And come by our poster at NeurIPS in San Diego: neurips.cc/virtual/2025...
#NeurIPS2025 #MachineLearningTheory #LLM #ChainOfThought
[10/10]
New Tsinghua study shows reasoning LLMs run faster but don’t out‑perform on tough tasks. Efficiency up, capability flat—what does this mean for RLVR and chain‑of‑thought tricks? Dive in for the data. #LLM #ChainOfThought #RLVR
🔗 aidailypost.com/news/study-f...
💭 Large language models sound like they reason — but what if that logic is a mirage?
A new Dispatch post explores why Chain-of-Thought breaks the moment data shifts.
🔗 The Mirage of Reasoning
open.substack.com/pub/ahmedkha...
#AIReasoning #ChainOfThought #LLMs #TheAKDispatch
A transparent engine with visible gears showing different thinking stages.
2/7: Step-by-Step Reasoning
Force clarity with "Think step by step."
❌ "Summarize this article"
✅ "First identify main claims, then evidence, then conclusion. Return summary after reasoning."
Watch the AI show its work like a math student.
#AIReasoning #ChainOfThought
🎧 A thought-provoking discussion on trust, transparency & reasoning.
🎬 YouTube: www.youtube.com/watch?v=xYb6...
🎙️ Spotify: open.spotify.com/episode/5JBN...
🍎 Apple: podcasts.apple.com/ca/podcast/c...
#WiAIR #WomenInAI #AIResearch #ExplainableAI #TrustworthyAI #ChainOfThought #NLP #LLM
CoT Referring improves multimodal referring expression tasks by 2.5%
A Chain-of-Thought training strategy parses descriptions into referring cues, improving performance by over 2.5% on RefCOCO, RefCOCO+ and RefCOCOg benchmarks. getnews.me/cot-referring-improves-m... #chainofthought #multimodal
SwiReasoning Switch-Thinking Boosts LLM Accuracy and Efficiency
SwiReasoning, a training‑free method, improves LLM accuracy by 1.5%–2.8% and boosts token efficiency up to 79% without extra fine‑tuning. Read more: getnews.me/swireasoning-switch-thin... #swireasoning #chainofthought #latentreasoning
Chain-of-Thought Strategies Boost Steerable Pluralistic AI Alignment
RLVR outperformed other chain‑of‑thought methods on the Value Kaleidoscope and OpinionQA benchmarks, achieving higher alignment with fewer training examples. getnews.me/chain-of-thought-strateg... #rlvr #chainofthought
FaithCoT-Bench: New AI Benchmark for Chain-of-Thought Faithfulness
FaithCoT‑Bench offers over 1,000 annotated CoT reasoning trajectories, with more than 300 flagged as unfaithful, covering four LLMs across four domains. Read more: getnews.me/faithcot-bench-new-ai-be... #faithcotbench #chainofthought
VLA-R1 Boosts Reasoning in Vision-Language-Action AI Models
Researchers introduced VLA-R1, a vision-language-action model that adds reasoning and rewards, and released the VLA-CoT-13K dataset with 13,000 chain-of-thought examples. Read more: getnews.me/vla-r1-boosts-reasoning-... #vlarmodel #chainofthought
Why Long Chain‑of‑Thought Training Can Harm Small Language Models
Training small language models with long chain‑of‑thought data can hurt performance: 8,000 long CoT samples caused up to a 75% drop, and 220,000 examples didn’t restore accuracy. Read more: getnews.me/why-long-chain-of-though... #slm #chainofthought
