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information lattice learning can be interpreted as a method for learning the structure of probabilistic graphical models by projecting probability distributions onto partition lattices and lifting rules back.
learn how lateral, semi, and anti joins solve problems that inner and left joins cannot handle cleanly.
mosaicleaks shows that deep research agents often expose private information when they search the web, and training them to be better at tasks makes the leakage worse.
pytorch's helion dsl uses llms to propose kernel configurations, matching bayesian optimization performance while exploring 10x fewer configs and cutting tuning time by 6.7x.
benchmarks show other parameter-efficient fine-tuning methods can beat lora on accuracy and memory, so it pays to test alternatives.
a new mathematical framework connects shock-wave theory to the learning dynamics of stochastic gradient descent after removing parameter symmetries.
a new method trains task generators using a lightweight probe instead of costly solver rollouts, making it practical to create frontier tasks for reinforcement learning.
a statistical theory for offline policy optimization using only trajectory-level outcome labels instead of per-step rewards.
a new attention method uses probabilistic routing through learned gaussian components to achieve linear-time sequence mixing, avoiding the quadratic cost of standard attention.
nominations are open until july 17, 2026 for awards recognizing contributors to pytorch, vllm, deepspeed, ray, helion, and safetensors.
a practical account of building a personal ai assistant with langchain and gpt-4o, focusing on memory, tools, and integration over off-the-shelf options.
a new open specification lets ai agents discover tools, skills, and other agents dynamically instead of needing them pre-installed.
molmomotion predicts future 3d object motion from video, points, and text instructions, outperforming existing methods and aiding robotics and video generation.
learn seven faster alternatives to row-by-row loops in pandas for common data transformations.
learn codex by building small, practical projects step by step, from a first app to a full-stack clone.
a diffusion-based method jointly models lab values and observation patterns to create realistic irregular clinical time series from mimic-iii data.
strands robots sdk integrates lerobot tools into a single agent loop for recording, simulation, policy inference, and hardware deployment.
glm-5.2 is an open-source model with a solid 1m-token context, improved coding, and flexible effort control, ranking highest among open models on long-horizon benchmarks.