depwignn-a-novel-approach-for-multi-hop-spatial-reasoning-in-text

analyzing-pure-demand-operational-semantics-for-program-analysis

analyzing-large-language-models-on-dynamic-graphs

an-open-programmable-multi-vendor-5g-o-ran-testbed-with-nvidia-arc-and-openairinterface-analysis

efficient-learning-of-structured-matrices-for-deep-neural-networks

optimizing-logical-execution-time-model-for-determinism-and-low-latency

mitigating-disparate-impact-of-pruning-in-sparse-models

unified-framework-for-error-analysis-of-physics-informed-neural-networks


Large Language Models (LLMs) can be harnessed to perform high-level reasoning tasks on long-term spatiotemporal sensor traces, leveraging their reasoning capabilities and world knowledge.


coremsg

harnessing-large-language-models-for-high-level-reasoning-over-long-term-spatiotemporal-sensor-traces


Harnessing Large Language Models for High-level Reasoning over Long-term Spatiotemporal Sensor Traces


title_rewrite

High-level reasoning on sensor traces