Destination
LLMs struggle with clinical reasoning and are just matching patterns, study finds

A new study in JAMA Network Open raises fresh doubts about whether large language models (LLMs) can actually reason through medical cases or if they're just matching patterns they've seen before. The researchers say these models aren't ready for clinical work.<br /> The article LLMs struggle with clinical reasoning and are just matching patterns, study finds appeared first on THE DECODER. [...]

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venturebeat
Microsoft built Phi-4-reasoning-vision-15B to know when to think — and when thinking is a waste of time

Microsoft on Tuesday released Phi-4-reasoning-vision-15B, a compact open-weight multimodal AI model that the company says matches or exceeds the performance of systems many times its size — while co [...]

Match Score: 185.31

venturebeat
Phi-4 proves that a 'data-first' SFT methodology is the new differentiator

AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]

Match Score: 110.15

venturebeat
Meta's new structured prompting technique makes LLMs significantly better at code review — boosting accuracy to 93% in some cases

Deploying AI agents for repository-scale tasks like bug detection, patch verification, and code review requires overcoming significant technical hurdles. One major bottleneck: the need to set up dynam [...]

Match Score: 104.42

venturebeat
New training method boosts AI multimodal reasoning with smaller, smarter datasets

Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning.The framewo [...]

Match Score: 103.03

venturebeat
Meta researchers open the LLM black box to repair flawed AI reasoning

Researchers at Meta FAIR and the University of Edinburgh have developed a new technique that can predict the correctness of a large language model's (LLM) reasoning and even intervene to fix its [...]

Match Score: 95.62

venturebeat
Large reasoning models almost certainly can think

Recently, there has been a lot of hullabaloo about the idea that large reasoning models (LRM) are unable to think. This is mostly due to a research article published by Apple, "The Illusion of Th [...]

Match Score: 94.87

venturebeat
New KV cache compaction technique cuts LLM memory 50x without accuracy loss

Enterprise AI applications that handle large documents or long-horizon tasks face a severe memory bottleneck. As the context grows longer, so does the KV cache, the area where the model’s working me [...]

Match Score: 82.19

venturebeat
Moonshot's Kimi K2 Thinking emerges as leading open source AI, outperforming GPT-5, Claude Sonnet 4.5 on key benchmarks

Even as concern and skepticism grows over U.S. AI startup OpenAI's buildout strategy and high spending commitments, Chinese open source AI providers are escalating their competition and one has e [...]

Match Score: 81.69

venturebeat
Google’s new AI training method helps small models tackle complex reasoning

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning task [...]

Match Score: 75.07