arXiv:2508.02039v2 Announce Type: replace
Abstract: Increasing concerns for data privacy and other difficulties associated with retrieving source data for model training have created the need for…
arXiv:2606.06214v1 Announce Type: cross
Abstract: Correctness and readability are key measures of code quality, respectively ensuring functional fidelity and ease of comprehension. While most…
arXiv:2606.04672v2 Announce Type: replace-cross
Abstract: Continuous-time dynamic graphs (CTDGs) provide a richer framework to capture fine-grained temporal patterns in evolving relational data….
arXiv:2606.06021v1 Announce Type: cross
Abstract: On-policy distillation (OPD) supervises the student only in output space by matching next-token probabilities. This output-only paradigm has two…
arXiv:2603.24747v2 Announce Type: replace
Abstract: The emergence of large language model agents capable of invoking external tools has created urgent need for formal verification of agent…
arXiv:2304.10891v3 Announce Type: replace-cross
Abstract: Transformer-based models are becoming a central paradigm in autonomous driving because they can capture long-range spatial dependencies,…
arXiv:2606.05008v1 Announce Type: cross
Abstract: As multi-modal models advance towards long-form video understanding, memory emerges as a critical capability. Despite substantial efforts in…
arXiv:2606.04845v1 Announce Type: cross
Abstract: Sequential decision-making problems are often modelled as a Markov decision process (MDP). We focus on the stochastic shortest path (SSP) problem,…
arXiv:2408.01382v3 Announce Type: replace
Abstract: Originating in game theory, Shapley values are widely used for explaining a machine learning model’s prediction by quantifying the contribution of…
arXiv:2605.29076v2 Announce Type: replace-cross
Abstract: LLMs have advanced text classification, yet existing paradigms face a trade-off: supervised (label only) fine-tuning is scalable but offers…