Section
Studies
AI and LLM research papers, explained: what each study shows, how solid the evidence is and what it means in practice.
FilterMoonshot AI
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Kimi K3: A 2.8T Open MoE With 2.5× Better Scaling Than K2
Moonshot’s Kimi K3 activates 104B of 2.8T params, adds native vision and 1M context. KDA, Attention Residuals and Stable LatentMoE deliver ~2.5× scaling efficiency over Kimi K2.
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Even Top Agents Finish Only ~30% of Real Startup Product Workflows
StartupBench, built from market-validated AI products: Kimi-K3 and GPT-5.6-sol average ~73.6% partial scores, but no model completes one-third…
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Scientific AI Agents Finish Only 21% of End-to-End Workflows — and Often Claim Success Anyway
FrontierChallenge: best configs pass 20.6% of 97 released science workflows. In electrochemistry, Avg. Score hits 94.9 with 0%…
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Top GUI Agents Clear Only 31% of Professional Long-Horizon Workflows
Workflow-GYM: Gemini-3.1-pro reaches 30.67% pass on domain-specific software workflows of 30–110 steps; most models’ pass@3 stays under 30%.
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Most Multi-Agent Setups Violate Safety Rules Mid-Run, Even When the Answer Looks Fine
HarnessAudit-Bench tests 210 tasks across 10 harness configs: more than half of multi-agent setups show trajectory violations that…
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Hidden AI Reasoning Can Be Decrypted by Cheaper Models, Researchers Show
Encrypted chain-of-thought blocks from Anthropic, OpenAI and Google APIs are interchangeable across models. Feeding them to a weaker model makes it print the reasoning, exposing 367…
Editor's picks
- Tampered ML: Even the Best AI Models Miss One in Five Planted Research Flaws
- Realistic MCP Faults Halve Agent Quality, and a Bigger Model Doesn’t Help
- Copilot Users Collaborate More, Not Less: Study of 12,000 Employees
- LLM Reviewers Send 76% of Published Top-Journal Papers Back, Yet Miss Most Planted Flaws