Research & technical reports

Anthropic engineer Sholto Douglas said Claude Mythos solved OpenAI’s Erdős unit distance conjecture problem over the weekend and produced a “cute simple proof”; the RSS snippet does not disclose the proof, verification process, or benchmark setup.

Runway released Project Luxo, showing AI shorts and ad samples including The Rogue; each work was made by a single-person team, with production times ranging from three weeks to four hours.

A Stanford-led study says candidates who fail AI hiring tests face systemic rejection across companies, but the RSS snippet does not disclose sample size, test design, vendors, or measured disparity rates.

Nanjing University LAMDA and Alibaba Intelligent Engine proposed DAR, a timestep-aware cross-layer routing method that replaces fixed residual accumulation in DiT; on ImageNet 256x256, it reduced SiT-XL/2 FID from 9.67 to 7.56 and reached baseline convergence quality with 8.75x fewer training iterations.

SkillOpt uses a frontier model to propose add, delete, and replace edits to markdown skill files, then accepts only strict gains on a held-out validation set; the best skills usually converge after 1 to 4 accepted edits.

Zhejiang University and Alibaba introduced Unified Thinker, an independent planning module trained with 40,000 HieraReason-40K samples and a two-stage GRPO reinforcement-learning setup that turns structured reasoning traces into executable visual instructions for image generation and editing.

Spatial-Agent inserts a GeoFlow Graph between natural-language questions and map tools, and Spatial-Agent with GPT-4o-mini reaches 45.15% accuracy on MapEval-API versus a 23.00% API baseline.

RTPurbo converts full-attention LLMs to sparse inference with a few hundred adaptation steps. It keeps the full KV cache only for retrieval heads, uses a 16-dimensional token indexer, and reports up to 9.36x prefill speedup at 1M context plus about 2.01x decode speedup on long-context and reasoning benchmarks.

OpenBMB released BitCPM-CANN, a 1.58-bit QAT training stack on Ascend NPU with 0.5B, 1B, 3B, and 8B models trained from scratch, where the 1B to 8B variants retain 95.7%–97.2% of full-precision MiniCPM4 performance across 11 benchmarks.

Visual Para-Thinker introduces a parallel thinking framework for vision-language models, using Pa-Attention and LPRoPE to isolate four visual reasoning paths and training on 163,000 question-answer pairs.

Verkor’s Design Conductor generated an ASAP7 7nm GDSII layout for the VerCore RISC-V CPU from a 219-word English spec in 12 hours, with no engineer in the design loop; the reported result scored 3,261 CoreMark at 1.48GHz, but it has not been fabricated and lacks cache implementation.

Zhejiang University and the University of Adelaide introduced FlashAR, using 0.05% of the original training data to reduce Emu3.5-Image-34B 512×512 generation latency from 130.10 seconds to 5.68 seconds, while GenEval changed from 80.48 to 80.29.

Yoshua Bengio’s team introduced GRAM, a generative recursive reasoning model that samples multiple latent trajectories; on Sudoku-Extreme, GRAM reached 97.0% accuracy with 16 recursive steps and 20 parallel samples, exceeding TRM’s 90.5% result at 320 serial recursive steps.

Anthropic says Project Glasswing used Claude Mythos Preview with about 50 partners to find more than 10,000 high or critical vulnerabilities in global critical systems, with independently verified accuracy of 90.6%.

ModelBest, Tsinghua University, and OpenBMB released BitCPM-CANN, a 0.5B-8B open model family trained natively on Huawei Ascend 910B NPUs with 1.58-bit ternary weights, cutting memory use by about 6x versus BF16 while retaining 95-97% of full-precision benchmark performance.

Researchers from The Hong Kong Polytechnic University and HKUST (Guangzhou) introduced ULSPB with 350 settings; routine conversations can poison an agent’s long-term state without malicious prompts, while StateGuard audits state diffs before persistence and reduces Harm Score to near zero in Targeted-Ensemble settings.

Westlake University and collaborators introduced HiF-VLA, a motion-centric VLA framework that extracts compact Motion vectors with codecs such as H.264 and uses a joint expert to predict future visual motion and generate action sequences, reporting 31.4GB peak memory and 117.7ms latency under the cited history-window setting.

Meta AI and the Chinese University of Hong Kong proposed ATLAS, a visual reasoning method that uses one Functional Token to connect Agentic and Latent Visual Reasoning, with ATLAS-178K, a two-stage SFT+RL pipeline, and LA-GRPO to train sparse visual-operation tokens.

An OpenAI general-purpose reasoning model refuted Erdős’s 1946 unit distance conjecture in the plane; the post says the model was not specially trained for mathematics, and Tim Gowers said he would recommend it to Annals of Mathematics.

arXiv 2605.20315 argues for W4A4 quantization during prefilling to target a theoretical 4x gain, while keeping decoding on the original high-precision path because activation errors can perturb sampled tokens and accumulate across autoregressive generation.