Zhemal Khamidun
Head of AI at Alpina Digital, CPO of AlpinaGPT (~30-person engineering & AI team). Founder of Vibe Academy & Hamidun Consulting, author of the AI channel «Готовим ИИшницу» (@jemal_hamidun).
RSIGame: a 27B model combo plays its own games and outperforms GPT-5.5
China's RSIGame has AI test, fix and refine games on its own. The authors claim a combination of 27B models beat GPT-5.5 in one-shot generation.
DecisionPivot Tests 40 Solver Models: Up to a 26-Point Gap at Equal Accuracy
DecisionPivot's 40,033-item benchmark shows two 27B models 2.6 points apart on the reference track diverge by 25.9 points on contrastive groups.
S-Agent 2.0 teaches a coding agent to understand 3D and beats SpatialClaw by 7.8 points
A ready-made coding agent with a set of 3D tools lifted Qwen3.8-27B to 66.5 on MMSI-Bench and 82.3 on ReVSI. Gemini-3.8-Flash reached 74.1 and 90.5.
TARSphere Tests MLLM-Powered Robots Across 360 Episodes in 30 Scenes
Agent Mosaic: LLM Agents Assemble Secrets From Harmless Documents in 7% of Responses
Layer Looping Cuts Diffusion LLM Training Costs by Up to 3.3x
FrontierCS 2 tested 12 AI agents on R&D tasks: the best passed 58%
SplatLab writes its own 3D Gaussian Splatting papers and beats baselines by up to +3.78 dB
An autonomous system reproduces a 3DGS paper, proposes an extension, trains models, and writes a manuscript. PSNR gains over baselines range from +0.18 to +3.78 dB.
Survey: Robots Are Learning to Improve Their Own Learning, but Evidence Is Still Missing
A new survey carries recursive self-improvement from code into the physical world and names four conditions under which robot gains accumulate instead of vanishing.
Quant-Arena: None of 9 LLMs Beat the A-Share Market in 2024
LASAGNA Tests 450 RAG Configurations: The Promised +47% Gain Turns Into Just +17%
LoopRec Picks Compute Depth for Each Item and Beats Baselines on 4 Backbones
RealMe Builds 2K Volumetric Video from a Handful of Cameras Using Diffusion
TraceForge trains models on "their own thoughts": +7.1 points on MBPP+
TraceForge writes reasoning for a closed model's answers in the student family's style. HumanEval+ gained 3.7 points, MBPP+ 7.1, and a judge scored the traces 0.68.
Researchers Propose PAPAV Framework: Only 3 of 64 Benchmarks Test Verification
A new paper compares computer-use agents and robots through five PAPAV functions. Of 64 benchmarks, 5 assess outcome prediction and only 3 assess result…