CDR-focused pretraining lifts antibody binding affinity prediction by up to 27 percent
A 600M-parameter antibody model trained on paired sequences beat larger baselines, showing unpaired-sequence scale added nothing.
Landmark Papers
What the papers actually said - linked to the originals.
686 entries, all primary-sourced
Demystifying Agent Skills: Why They Work Until They Don't
An 8,135-trial study finds agent skills work as procedural anchors, but retrieval precision collapses from 29.6 to 3.3 percent as pools grow.
StateM: harness scaling on Terminal-Bench 2.1
A runtime harness lifts GPT-5.6 Sol to 95.3 percent on Terminal-Bench 2.1 for about 15 dollars, without touching model weights.
FreeToken: edge-native mixture-of-experts serving
A Berkeley-led system serves mixture-of-experts models up to 753B parameters on a single personal machine with an 8GB GPU.
Claude designs protein binders against 14 of 15 targets
Anthropic reports Claude autonomously designed 354 confirmed protein binders from 1,320 designs, succeeding on 14 of 15 targets.
Microsoft broadens access to Skala 1.1, a machine-learned density functional
Microsoft Research shipped Skala 1.1, trained on 2.5 times more data, reporting 2.8 kcal/mol weighted average error on GMTKN55.
Demystifying Reinforcement Learning Post-Training of Language Models
A controlled study of RL with verifiable rewards finds the base model prior, not reward design, decides success.
JoyAI-Echo-1.5: Long-Horizon Audio-Visual Generation for Persistent Stories
A unified audio-visual generator that holds character appearance and voice identity steady across many shots.
Automated Researchers Can Reliably Mitigate Alignment Failures
Anthropic reports Claude closed 26 to 96 percent of ten measured safety gaps while running the research loop itself.
SMELT: Scaling Laws for Compute-Matched Looped Mixture-of-Experts Transformers
Looping the middle layers of a sparse MoE Transformer twice saves 6.8 to 18 percent of training FLOPs at 54B scale.
A Bayesian optimization framework cuts scaling-law construction cost by up to 100x
A new method fits foundation-model scaling laws using Bayesian optimization and surrogate evaluations, cutting required training runs by 10 to 100 times
Leading reasoning models are chaotic dynamical systems with fractal decision basins
Researchers show reasoning models trace fractal basin boundaries when solving hard problems, explaining why extra reasoning time is unavoidable
ARCHE pairs a reasoning model with computational chemistry to validate reaction mechanisms
ARCHE combines a reasoning model, a chemistry-specialized model and lab tools to propose and validate reaction mechanisms autonomously
New benchmark finds AI agents score 1 to 15.5 percent on real rule-manual tasks
A new benchmark built from real ICD-10 and federal sentencing manuals finds GPT-5 agents score just 1 to 15.5 percent exact match