#llmreasoning — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #llmreasoning, aggregated by home.social.
-
New research shows AI agents can map an entire plan, execute each step, then pause to reflect and re‑plan if needed. This iterative loop boosts LLM reasoning and autonomous problem solving, bringing us closer to truly self‑directed agents. Dive into the details of this planning‑reflection pattern and its open‑source implications. #AIAgents #IterativeLearning #LLMReasoning #AutonomousAgents
🔗 https://aidailypost.com/news/ai-agents-map-full-plans-execute-steps-then-pause-replan-if-needed
-
New research shows AI agents can map an entire plan, execute each step, then pause to reflect and re‑plan if needed. This iterative loop boosts LLM reasoning and autonomous problem solving, bringing us closer to truly self‑directed agents. Dive into the details of this planning‑reflection pattern and its open‑source implications. #AIAgents #IterativeLearning #LLMReasoning #AutonomousAgents
🔗 https://aidailypost.com/news/ai-agents-map-full-plans-execute-steps-then-pause-replan-if-needed
-
New research shows AI agents can map an entire plan, execute each step, then pause to reflect and re‑plan if needed. This iterative loop boosts LLM reasoning and autonomous problem solving, bringing us closer to truly self‑directed agents. Dive into the details of this planning‑reflection pattern and its open‑source implications. #AIAgents #IterativeLearning #LLMReasoning #AutonomousAgents
🔗 https://aidailypost.com/news/ai-agents-map-full-plans-execute-steps-then-pause-replan-if-needed
-
RLVR promises faster sampling but leaves reasoning untouched—base LLMs still carry the heavy‑lifting of trajectories. The paper (NeurIPS 2025) shows that gains come from smarter teacher‑distillation and minor architectural tweaks, not a new reasoning engine. Curious how sampling efficiency separates from true understanding? Dive into the details. #RLVR #SamplingEfficiency #LLMReasoning #NeurIPS2025
🔗 https://aidailypost.com/news/rlvr-lifts-sampling-efficiency-not-reasoning-base-models-hold
-
Quoting Andrej Karpathy In 2025, Reinforcement Learning from Verifiable Rewards (RLVR) emerged as the de facto new major stage to add to this mix. By training LLMs against automatically verifiable ...
#andrej-karpathy #llm #generative-ai #llm-reasoning #definitions #ai #llms #deepseek
Origin | Interest | Match -
deepseek-ai/DeepSeek-Math-V2 deepseek-ai/DeepSeek-Math-V2 New on Hugging Face, a specialist mathematical reasoning LLM from DeepSeek. This is their entry in the space previously dominated by propri...
#mathematics #ai #generative-ai #llms #llm-reasoning #deepseek #llm-release #ai-in-china
Origin | Interest | Match -
Kimi K2 Thinking Kimi K2 Thinking Chinese AI lab Moonshot's Kimi K2 established itself as one of the largest open weight models - 1 trillion parameters - back in July . They've now released...
#ai #generative-ai #llms #llm #mlx #pelican-riding-a-bicycle #llm-reasoning #llm-release #openrouter #ai-in-china #artificial-analysis
Origin | Interest | Match -
Kimi K2 Thinking Kimi K2 Thinking Chinese AI lab Moonshot's Kimi K2 established itself as one of the largest open weight models - 1 trillion parameters - back in July . They've now released...
#ai #generative-ai #llms #llm #mlx #pelican-riding-a-bicycle #llm-reasoning #llm-release #openrouter #ai-in-china #artificial-analysis
Origin | Interest | Match -
Kimi K2 Thinking Kimi K2 Thinking Chinese AI lab Moonshot's Kimi K2 established itself as one of the largest open weight models - 1 trillion parameters - back in July . They've now released...
#ai #generative-ai #llms #llm #pelican-riding-a-bicycle #llm-reasoning #llm-release #openrouter #ai-in-china #artificial-analysis #moonshot
Origin | Interest | Match -
Simple Prompt Tweaks Derail LLM Reasoning - MarkTechPost
➡️ MIT researchers analyzed how input changes impact the response quality of 13 prominent LLMs.
➡️Prompt perturbations included irrelevant contexts, misleading (pathological) instructions, and a mix of additional yet unnecessary details.
➡️Quality dropped substantially, with average declines of up to 55.89% for irrelevant contexts. -
Simple Prompt Tweaks Derail LLM Reasoning - MarkTechPost
➡️ MIT researchers analyzed how input changes impact the response quality of 13 prominent LLMs.
➡️Prompt perturbations included irrelevant contexts, misleading (pathological) instructions, and a mix of additional yet unnecessary details.
➡️Quality dropped substantially, with average declines of up to 55.89% for irrelevant contexts. -
Simple Prompt Tweaks Derail LLM Reasoning - MarkTechPost
➡️ MIT researchers analyzed how input changes impact the response quality of 13 prominent LLMs.
➡️Prompt perturbations included irrelevant contexts, misleading (pathological) instructions, and a mix of additional yet unnecessary details.
➡️Quality dropped substantially, with average declines of up to 55.89% for irrelevant contexts. -
Simple Prompt Tweaks Derail LLM Reasoning - MarkTechPost
➡️ MIT researchers analyzed how input changes impact the response quality of 13 prominent LLMs.
➡️Prompt perturbations included irrelevant contexts, misleading (pathological) instructions, and a mix of additional yet unnecessary details.
➡️Quality dropped substantially, with average declines of up to 55.89% for irrelevant contexts. -
Simple Prompt Tweaks Derail LLM Reasoning - MarkTechPost
➡️ MIT researchers analyzed how input changes impact the response quality of 13 prominent LLMs.
➡️Prompt perturbations included irrelevant contexts, misleading (pathological) instructions, and a mix of additional yet unnecessary details.
➡️Quality dropped substantially, with average declines of up to 55.89% for irrelevant contexts. -
Unlocking Human-like Reasoning in AI: The Meta Chain-of-Thought Breakthrough
In an ambitious leap forward, researchers introduce the Meta Chain-of-Thought framework, aiming to enhance reasoning capabilities in large language models (LLMs). This innovative approach not only bui...
#news #tech #MetaChainOfThought #LLMReasoning #AIAdvancements
-
Unlocking Human-like Reasoning in AI: The Meta Chain-of-Thought Breakthrough
In an ambitious leap forward, researchers introduce the Meta Chain-of-Thought framework, aiming to enhance reasoning capabilities in large language models (LLMs). This innovative approach not only bui...
#news #tech #MetaChainOfThought #LLMReasoning #AIAdvancements
-
Unlocking Human-like Reasoning in AI: The Meta Chain-of-Thought Breakthrough
In an ambitious leap forward, researchers introduce the Meta Chain-of-Thought framework, aiming to enhance reasoning capabilities in large language models (LLMs). This innovative approach not only bui...
#news #tech #MetaChainOfThought #LLMReasoning #AIAdvancements
-
Unlocking Human-like Reasoning in AI: The Meta Chain-of-Thought Breakthrough
In an ambitious leap forward, researchers introduce the Meta Chain-of-Thought framework, aiming to enhance reasoning capabilities in large language models (LLMs). This innovative approach not only bui...
#news #tech #MetaChainOfThought #LLMReasoning #AIAdvancements
-
Unlocking Human-like Reasoning in AI: The Meta Chain-of-Thought Breakthrough
In an ambitious leap forward, researchers introduce the Meta Chain-of-Thought framework, aiming to enhance reasoning capabilities in large language models (LLMs). This innovative approach not only bui...
#news #tech #MetaChainOfThought #LLMReasoning #AIAdvancements
-
Four papers on LLM reasoning summarized by @melaniemitchell https://aiguide.substack.com/p/the-llm-reasoning-debate-heats-up along with the background in her latest. Of these, the chain of thought prompting paper's attempt to identify sources of predictions (memorization vs reasoning] is very interesting, although chaotic. Stats people might hate the conclusions. #LLMReasoning #LLMResearch
-
Four papers on LLM reasoning summarized by @melaniemitchell https://aiguide.substack.com/p/the-llm-reasoning-debate-heats-up along with the background in her latest. Of these, the chain of thought prompting paper's attempt to identify sources of predictions (memorization vs reasoning] is very interesting, although chaotic. Stats people might hate the conclusions. #LLMReasoning #LLMResearch
-
Four papers on LLM reasoning summarized by @melaniemitchell https://aiguide.substack.com/p/the-llm-reasoning-debate-heats-up along with the background in her latest. Of these, the chain of thought prompting paper's attempt to identify sources of predictions (memorization vs reasoning] is very interesting, although chaotic. Stats people might hate the conclusions. #LLMReasoning #LLMResearch
-
Four papers on LLM reasoning summarized by @melaniemitchell https://aiguide.substack.com/p/the-llm-reasoning-debate-heats-up along with the background in her latest. Of these, the chain of thought prompting paper's attempt to identify sources of predictions (memorization vs reasoning] is very interesting, although chaotic. Stats people might hate the conclusions. #LLMReasoning #LLMResearch
-
Four papers on LLM reasoning summarized by @melaniemitchell https://aiguide.substack.com/p/the-llm-reasoning-debate-heats-up along with the background in her latest. Of these, the chain of thought prompting paper's attempt to identify sources of predictions (memorization vs reasoning] is very interesting, although chaotic. Stats people might hate the conclusions. #LLMReasoning #LLMResearch