Cell-preservation technique could make CAR-T cell therapy more accessible
MIT researchers’ approach, which uses naturally occurring sugars as antifreeze, could make it easier for hospitals to deploy this type of cancer treatment.
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Towards Unified Approaches in Self-Supervised Event Stream Modeling: Progress and Prospects
arXiv:2502.04899v3 Announce Type: replace Abstract: The proliferation of digital interactions across diverse domains, such as healthcare, e-commerce, gaming, and finance, has resulted in the generation of vast volumes of event stream (ES) data. ES data comprises continuous sequences of timestamped…
Solvable Sokoban Without a Solver via Diffusion
arXiv:2608.15958v1 Announce Type: cross Abstract: Deciding whether a Sokoban puzzle is solvable is PSPACE-complete (Culberson, 1997): solutions can be exponentially long and there is no short certificate to check. Solvability is also a fragile property, since even a single misplaced…
Improved Regret Analysis for Parallel Gaussian Process Bandit Optimization
arXiv:2608.16492v1 Announce Type: cross Abstract: This paper studies the regret analysis for parallel Gaussian process (GP) bandit optimization. The known regret upper bounds for the widely used GP batched upper confidence bound and GP batched Thompson sampling (GP-BTS) suffer from…
Explaining Reinforcement Learning Decisions in Self-adaptive Systems
arXiv:2608.14620v1 Announce Type: new Abstract: Reinforcement Learning (RL) has been extensively used in autonomous and self-* systems, but RL policies, especially deep RL ones relying on neural networks, lack transparency and are difficult to understand. This can lead to diminished…
Cell-preservation technique could make CAR-T cell therapy more accessible
MIT researchers’ approach, which uses naturally occurring sugars as antifreeze, could make it easier for hospitals to deploy this type of cancer treatment.
DeltaLog: Deferred Materialization of Recurrent States for Linear Attention Decoding
arXiv:2608.15533v1 Announce Type: cross Abstract: Linear attention models eliminate the quadratic prefix computation and context-growing KV cache of softmax attention by replacing pairwise token interactions with recurrent state updates. However, existing decoding implementations often materialize and write back the full…
Speculative Rollback Correction for Quality-Diverse Web Agent Imitation
arXiv:2606.12485v2 Announce Type: replace Abstract: Training interactive web agents through imitation learning from expert trajectories has emerged as a highly effective approach. However, determining the optimal timing for expert intervention presents a critical challenge in this context. Delayed intervention often…
Calibrated Trust, Not Sharper Prediction: An Empirical Test of Uncertainty Fusion
arXiv:2608.14617v1 Announce Type: new Abstract: A recurring proposal in legal AI is to improve case-outcome prediction by fusing uncertainty tools (evidence graphs with belief propagation, sequential Bayesian odds updating, Dempster-Shafer combination, and conformal prediction) into one pipeline. We test this…
PIKFNO: An Interpretable Neural Operator Based on Physics Informed Kernel Function
arXiv:2608.14619v1 Announce Type: new Abstract: This work proposes a new interpretable neural operator framework, termed the Physics Informed Kernel Function Neural Operator (PIKFNO), which explicitly incorporates physics informed kernel functions derived from governing equations into the neural operator architecture. Unlike…