SuperMimic Cuts Humanoid Whole-Body Training Compute by 1000x
A single differentiable world model lets one policy learn from large human-motion datasets on a single GPU, versus days on a cluster.
Preprints and papers, rewritten in plain English.
A single differentiable world model lets one policy learn from large human-motion datasets on a single GPU, versus days on a cluster.
A new benchmark called CETBench probes whether large language models can recognise functionally equivalent code after simple transformations, an ability the paper says is important for code rewriting.
A new arXiv proposal argues that aggregate success rates mask stage-level failures in long-horizon household robotics.
A transfer learning model finds common imaging-derived morphometric biomarkers across Alzheimer's and Parkinson's, improving diagnosis on small datasets.
A decade after the original audit, the share of Sequence Read Archive experiments with complete protocol annotation in the designated field has fallen, though additional terms appear in description fields.
A new Python toolkit provides a unified framework for relating single-neuron selectivity, population activity, and network dynamics to behavioral measures, validated on hippocampal recordings and simulations.
A new benchmark uses marine mammal vocalizations to test whether audio-language models can reason about unfamiliar sounds from fine-grained acoustic cues, and finds they lag far behind humans.
A new quantization scheme recovers speaker timbre lost by standard 4-bit compression of text-to-speech diffusion transformers, without retraining.
A deep learning model can localize upper airway obstructions from snoring audio, offering a non-invasive alternative to endoscopic exams.
A learned 'abstract compression' replaces prior-turn audio with fixed latent tokens, recovering much of the accuracy gain of raw context at lower cost.
A new training strategy helps generative models explore synonymous codon sequences more efficiently, producing diverse mRNA candidates for target proteins.
A new low-rank adaptation method organizes experts by phonetic categories rather than accent, improving zero-shot accented English recognition.
A small routing module that matches separated speech streams to fixed speaker identities before diffusion cuts wrong-track time from 43.9% to 4.1% on remote conversations.
A new study finds that generation in self-supervised audio representation spaces can match or beat dedicated text-to-audio latent spaces, challenging reconstruction quality as the key metric.
Researchers identify shared neurons that align audio and text, revealing how large audio-language models recognize acoustic attributes.
A new audio-centric approach lets UAVs follow spoken commands to segment targets in aerial images faster and more accurately than text-based methods.
A new benchmark reveals that large audio-language models often locate relevant sounds but fail to interpret them reliably, especially on ordering and counting tasks.
A 1,280-run sensitivity study finds skewed input influence and flags operator-actionable failure modes in an open-source adult physiology simulator.