LoRA, PEFT, instruction tuning and domain adaptation — adapting a pretrained model without paying to train one.
arXiv:2611.05892v1 Announce Type: cross Abstract: A learned cost model that predicts query runtimes is trained on measurements from one machine. When the database moves to other hardware, its plans s...
arXiv:2611.05901v1 Announce Type: cross Abstract: Developers insert logging statements in source code to record its execution, and the resulting logs are essential for detecting and troubleshooting s...
arXiv:2611.06096v1 Announce Type: cross Abstract: Can hyperspectral (HS) imaging be used to predict the elemental composition of physical specimens found on the Earth's surface? We approach this prob...
arXiv:2601.06641v4 Announce Type: replace Abstract: Membership inference attacks (MIAs) pose a serious privacy threat in federated learning (FL). While MIAs have been extensively studied in standard...
arXiv:2602.05943v2 Announce Type: replace Abstract: Merging finetuned Large Language Models (LLMs) has become increasingly important for integrating diverse capabilities into a single unified model....
arXiv:2603.08462v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting improves LLM accuracy on complex tasks but often increases token usage and inference cost. Existing ``Budget Forci...
arXiv:2611.02170v2 Announce Type: replace Abstract: Diffusion models are often inaccurate in critical, data-sparse regions of the target distribution. Sampling from restrained distributions, biased d...
arXiv:2107.12636v5 Announce Type: replace-cross Abstract: Detection transformers have recently shown promising object detection results and attracted increasing attention. However, how to develop eff...
arXiv:2611.05539v1 Announce Type: new Abstract: LLMs can repair noisy OCR transcripts of historical documents, but they also change text that was already correct. We propose EditVeto, a veto gate pla...
arXiv:2611.05596v1 Announce Type: new Abstract: Different retrievers exist for retrieval-augmented generation, yet none performs best for all queries. Therefore, the key question is: given a query an...
arXiv:2512.20773v5 Announce Type: replace Abstract: Realistic user simulation is crucial for training and evaluating multi-turn dialogue systems, yet creating simulators that accurately replicate hum...
arXiv:2606.17973v2 Announce Type: replace Abstract: Depression is a leading cause of disability worldwide, yet validated questionnaires such as the Patient Health Questionnaire-9 (PHQ-9) often go unc...
arXiv:2611.05451v1 Announce Type: new Abstract: While discrete tokenization in Unified Multimodal Models (UMMs) establishes strong semantic reasoning, it introduces a strict quantization bottleneck t...
arXiv:2611.05734v1 Announce Type: new Abstract: Owing to the prohibitive cost of manual annotation for enormous medical images, self-supervised learning (SSL) has gained substantial attention and sho...
arXiv:2611.05811v1 Announce Type: new Abstract: Recent pansharpening models achieve strong fusion performance on trained sensors, yet often generalize poorly to unseen sensors. Existing cross-sensor...
arXiv:2611.05974v1 Announce Type: new Abstract: For decades, diagnostic pathology has relied on thin two-dimensional (2D) tissue sections, despite biological tissues exhibiting inherently three-dimen...
arXiv:2611.06302v1 Announce Type: new Abstract: Fine-grained action understanding requires vision-language models to ground what an agent does, how it acts, and why it acts in spatio-temporal evidenc...
arXiv:2611.06849v1 Announce Type: new Abstract: State-of-the-art feedforward reconstruction models perform poorly on in-the-wild object-centric photo collections. They are trained largely on single-s...
arXiv:2611.06453v1 Announce Type: cross Abstract: Closed-loop driving benchmarks in CARLA rank agents by a driving score that multiplies route completion by an infraction penalty. This score does not...
arXiv:2503.15846v4 Announce Type: replace Abstract: Dynamic Scene Graph Generation (DSGG) aims to capture objects and their evolving relations in videos. Despite recent progress, the practicality and...