Search papers, labs, and topics across Lattice.
7
0
11
EEVEE's innovative router-prompt co-evolution strategy enables LLMs to thrive in diverse, real-world task environments, outperforming existing methods by up to 48.2%.
Achieving 100% success on challenging theorem proving tasks, Goedel-Architect redefines efficiency in formal proofs by leveraging natural language guidance and adaptive blueprint refinement.
Success in long-horizon tasks hinges more on an agent's iterative persistence than on the quality of its initial solution.
Nemotron 3 Super proves you can achieve comparable accuracy to existing 120B models, but with significantly higher inference throughput, by combining Mamba, Attention, and Mixture-of-Experts.
Exact sampling in large-vocabulary decoding can be sped up by 19% simply by fusing it into the LM-head matmul, turning a bandwidth bottleneck into a lightweight epilogue.
AI agents that ace isolated coding tasks fall apart when faced with the messy reality of continuous software evolution, dropping from 80% to 38% success rates in a new benchmark.
Forget finetuning on curated datasets – OpenClaw-RL lets agents learn directly and continuously from *every* interaction, turning user replies, tool outputs, and even GUI changes into valuable RL signals.
