For An Exciting Tomorrow
arXiv:2505.00661v3 Announce Type: replace-cross Abstract: Large language models exhibit exciting capabilities, yet can show surprisingly narrow generalization from finetuning. E.g.…
arXiv:2511.08012v1 Announce Type: cross Abstract: Direction-of-Arrival (DOA) estimation is critical in spatial audio and acoustic signal processing, with wide-ranging applications…
arXiv:2511.07295v2 Announce Type: replace-cross Abstract: Implicit feedback, employed in training recommender systems, unavoidably confronts noise due to factors such as…
arXiv:2511.08086v1 Announce Type: cross Abstract: The use of learned dynamics models, also known as world models, can improve the sample…
arXiv:2511.08087v1 Announce Type: cross Abstract: Evaluating identity preservation in generative models remains a critical yet unresolved challenge. Existing metrics rely…
arXiv:2511.07392v2 Announce Type: replace-cross Abstract: In da Vinci robotic surgery, surgeons’ hands and eyes are fully engaged in the procedure,…
arXiv:2511.07436v1 Announce Type: new Abstract: The integration of AI tools into medical applications has aimed to improve the efficiency of…
arXiv:2511.06696v1 Announce Type: cross Abstract: Pretrained equivariant graph neural networks based on spherical harmonics offer efficient and accurate alternatives to…
arXiv:2511.05459v2 Announce Type: replace-cross Abstract: Evaluating large language models (LLMs) for software engineering has been limited by narrow task coverage,…
arXiv:2511.05524v1 Announce Type: new Abstract: LLM-based autonomous research agents report false claims: tasks marked “complete” despite missing artifacts, contradictory metrics,…