Reinforcement learning (RL) in Partially Observable Markov Decision Processes (POMDPs) is computationally challenging due to the curse of long-range dependence on history. Fortunately, recent studies have shown that a range of POMDPs that satisfy the filter stability assumption can be well approximated by a superstate...
Jingjuan Huang, Zhiyao Zhang, Alvaro Velasquez et al.· 0 citations
Few-shot adaptation of vision-language models must balance two competing goals: learning fine-grained visual distinctions from very limited supervision and preserving the efficiency that makes frozen CLIP-like models attractive for deployment. Existing lightweight adaptation methods, including prompt tuning, LoRA, and...
Mohammed Rahman Sherif Khan Mohammad, Ardhendu Behera, Sandip Pradhan et al.· 0 citations
Skin lesion segmentation without annotated masks requires the target to be specified through other cues. Existing approaches rely on dermoscopy-specific rules, annotation-derived model priors, or user-selected regions. A general text-to-image diffusion transformer offers a text interface to the target, but its concept-...
Hongyu Cao, Guangfu Guo, Jinghan Zhang et al.· 0 citations
Genetic variants are routinely reclassified in ClinVar after a patient is tested, sometimes from uncertain to pathogenic, yet patient recontact is inconsistent, with no clear duty and responsibility diffused among labs, providers, and patients. Many affected people discuss their results in public online health communit...
Kamalakkannan Ravi, Mengshu Nie, Annapurna Poduri et al.· 0 citations
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Transductive adaptation improves vision-language models at test time by refining predictions on an unlabeled batch, but current methods face a key trade-off. Aggressive approaches exploit batch structure but can drift when batches are sparse, have prior shift, or cover little of the label space. Conservative methods be...
Mohammed Rahman Sherif Khan Mohammad, Ardhendu Behera, Sandip Pradhan et al.· 0 citations
Forecasting foundation models are increasingly used as frozen feature extractors for time series classification, but it remains unclear whether their pretrained representations offer an advantage over strong classifiers that do not require pretraining. This raises an important question: do these representations provide...
Rishit Jain, Rishit Kar, Chetashri Bhadane et al.· 0 citations
LLM-based proactive dialogue systems provide goal-directed support through sustained interaction. Fine-tuning their underlying models on externally supplied dialogue data introduces backdoor risks. Existing LLM backdoor studies primarily focus on eliciting an attacker-specified response upon trigger activation. We pres...
Continuous integration and AI-assisted review spend the same budget on every commit, although few commits introduce bugs. We study KG-AST, which scores each commit risk from git history and code-graph features before heavy tests or AI review run, so the budget goes to the riskiest commits first, and which hands the AI...
Alexander Lerchner's recent work on the 'abstraction fallacy' argues that computational functionalism confuses physical processes with abstract descriptions, and that symbolic computation alone cannot instantiate consciousness. Yet these claims were anticipated by Korzybski's map-territory distinction, Searle's critiqu...
Across four independent cohorts, BrainPFN beats KRR on small sample prediction, and leads recent foundation models pre-trained at four to nine times larger scale, showing that a modest, openly available pool can match or beat models trained at Biobank scale.
Carlo Alberto Barbano, Demian Wassermann· 0 citations
Oscillatory phase coding (OPC) is widely observed in neural systems and has been implicated in cognitive functions such as memory and sequence processing. However, its computational role and neural substrates remain largely unclear. Here, we studied OPC by training recurrent neural networks (RNNs) with adaptation to pe...
Kehan Lu, Tianhao Chu, Aiersi Tuerhong et al.· 0 citations
Background. A connectome specifies the substrate available to a nervous system, not how much of it a given computation requires. Reported compact sufficient circuits are point estimates: one subset, one task, one fidelity threshold, one parameterisation. Methods. We formalise computational sufficiency as a cost-indexed...
Ali Mahdavi, Azadeh Zamanifar, Amirfarhad Farhadi et al.· 0 citations
