Search papers, labs, and topics across Lattice.
Affiliation:
7
0
9
2
SWIM redefines list evaluation by modeling user engagement as a survival process, leading to substantial gains in recommendation effectiveness.
Achieving duplicate-free item selection in recommendation systems without sacrificing efficiency, DIRECTOR revolutionizes how we approach reranking by leveraging transport-optimized retrieval.
Pair-Space Generation achieves up to 4x faster generative reranking while enhancing user engagement on platforms with over 400 million daily users.
UMA achieves remarkable multi-task performance by seamlessly linking object motion and robot actions, outperforming specialized models without manual task instructions.
Current autonomous AI agents are alarmingly unprepared for real-world adversarial attacks, often missing critical vulnerabilities in dynamic environments.
FlashEvaluator slashes the computational cost of evaluating multiple sequences in Generator-Evaluator frameworks while boosting accuracy by enabling direct cross-sequence comparisons.
SVD-Attention slashes the quadratic cost of attention to linear for recommendation tasks by exploiting the inherent low-rank structure of user behavior sequences, without sacrificing softmax.
