Search: “research”

arXiv:2609.17535v1 Announce Type: new Abstract: Language generation research increasingly spans three paradigms: autoregressive decoding, discrete masked diffusion, and continuous flow-matching. Compa

I'm at a crossroads with two grad school options that would take me in somewhat different research directions, and I wanted some general advice on these fields, their growth, and industry alignment. I

On a sunny July day in Berkeley, California, the country's top AI safety researchers gathered on an unmarked floor of an unmarked building. They had come together for a 'war room' to dissect the high-

arXiv:2609.18154v1 Announce Type: cross Abstract: We describe our system for LitTraceQA (GroundLM @ EMNLP 2026): given a research question, retrieve the relevant papers from a pool of 27,487, cite the

arXiv:2609.16207v1 Announce Type: new Abstract: Spatial Transcriptomics (ST) has transformed biomedical research by enabling the spatial mapping of gene expression across tissue sections. However, hig

arXiv:2507.06445v4 Announce Type: replace-cross Abstract: Interpretability research often predicts model responses to targeted mechanistic interventions. But can we predict responses to unseen input d

arXiv:2609.14384v1 Announce Type: new Abstract: What must a neural system be capable of to implement language? Current research annotates stimuli with linguistic variables and tests which electrodes,

arXiv:2609.13281v1 Announce Type: cross Abstract: Ocean-bottom seismometers (OBS), originally deployed for geophysical research, continuously record low-frequency sound for months to years across broa

arXiv:2609.14099v1 Announce Type: cross Abstract: Formal explainability of classifying neural networks (NNs) is an active area of research, providing explanations with provable guarantees of the class

arXiv:2609.14412v1 Announce Type: new Abstract: Deep research agents answer complex questions through iterative loops of searching, reading, and reasoning. Recent work on reasoning-intensive benchmark

arXiv:2404.07729v2 Announce Type: replace-cross Abstract: Continual learning (CL) evaluates adaptability in learning solutions to retain knowledge. Our research addresses the challenge of catastrophic

arXiv:2609.13031v1 Announce Type: new Abstract: With the recent rise and adoption of tabular foundation models, optimizing their inference performance becomes an emerging field for efficiency research

arXiv:2609.12342v1 Announce Type: new Abstract: The conditional generation of 3D motion has emerged as a key research topic due to its wide applicability across robotics, AR/VR, gaming, and content cr

arXiv:2609.11373v1 Announce Type: cross Abstract: Empirical research on content moderation is fundamentally constrained by the opaque deployment of moderation systems on major social media platforms.

The resignation this week of Anthropic researcher Jacob Coxon over concerns that artificial intelligence labs are “gambling with our lives” lit up the long-smoldering argument about whether AI is head

arXiv:2603.04199v2 Announce Type: replace-cross Abstract: Theoretical and applied research into privacy encompasses an incredibly broad swathe of differing approaches, emphases and aims. This work int

arXiv:2603.15203v1 Announce Type: cross Abstract: Nuclear mass prediction is one of the core issues in nuclear physics research, yet it faces the challenge of small-sample datasets with high complexit

arXiv:2609.07353v1 Announce Type: new Abstract: Large language models (LLMs) are used to simulate human participants in psychological research. We asked whether LLMs that reproduce human evaluations o

arXiv:2603.23114v2 Announce Type: replace Abstract: A human's moral decision depends heavily on the context. Yet research on LLM morality has largely studied fixed scenarios. We address this gap by in

arXiv:2507.21831v2 Announce Type: replace-cross Abstract: LLMs are seeing widespread use for task automation, including automated coding in the social sciences. However, even though researchers have p

arXiv:2609.07460v1 Announce Type: new Abstract: Uncertainty arising from inter-observer variability in medical image segmentation plays an important role in developing treatment plans. Research in thi

arXiv:2609.07155v1 Announce Type: new Abstract: Model compression is key to mitigate deployment challenges of ever growing machine learning models. In this area of research, singular value decompositi

We are at a watershed moment. The vibe is shifting. It's not over yet! We can still stop ASI! This week an Anthropic researcher quit, warning AI companies are 'gambling with our lives', and ControlAI'

arXiv:2603.21438v3 Announce Type: replace Abstract: To discover the weaknesses of LLMs, researchers often embed prompts into a vector space and cluster them to extract insightful patterns. However, ve

arXiv:2410.23440v4 Announce Type: replace Abstract: Operator learning, the approximation of mappings between infinite-dimensional function spaces using machine learning, has gained increasing research

arXiv:2609.03930v1 Announce Type: new Abstract: Existing research has repeatedly observed the tendency for English loanwords to cluster in the masculine gender across different recipient languages, ye

arXiv:2609.03515v1 Announce Type: new Abstract: Decoding-time KV cache compression research focuses heavily on designing better token scoring functions, while the temporal rule that aggregates scores

arXiv:2406.16893v3 Announce Type: replace-cross Abstract: The emergence of Transformer-based Large Language Models (LLMs) has substantially augmented the capabilities of Natural Language Processing (N

arXiv:2609.02620v1 Announce Type: new Abstract: Generative AI is changing how cultural artifacts are created and circulated, and with it our understanding of creativity itself. Researchers disagree ab

arXiv:2609.02272v1 Announce Type: cross Abstract: Faithfully translating research papers into repository-level implementations remains challenging because papers often describe methods at a high level

arXiv:2609.01671v1 Announce Type: cross Abstract: Security teams and researchers choose knowledge-graph extraction tooling for threat reports on the strength of published triple-F1 scores, yet those s

arXiv:2609.00231v1 Announce Type: new Abstract: Existing research on object hallucination in multimodal large language models (MLLMs) predominantly attributes the problem to language priors such as ov

arXiv:2609.01273v1 Announce Type: new Abstract: Synthetic data has become a common component of machine learning research. While widely adopted, its use in privacy-sensitive contexts has quietly shift

arXiv:2606.18237v2 Announce Type: replace-cross Abstract: Reproducing research results from papers and released code is central to scientific progress. Existing works have introduced benchmarks to eva

BenchMIRT is a new method for auditing LLM benchmarks question by question, revealing which capabilities they actually measure and helping researchers build smaller, more focused, and easier-to-interp

arXiv:2608.29348v1 Announce Type: new Abstract: Background: Patient details and acquisition metadata are important for clinical decisions, image quality control, and automated research pipelines, but

arXiv:2608.29388v1 Announce Type: cross Abstract: Recent machine learning research has increasingly focused on equilibrium analysis in non-cooperative games rather than solely on optimal solutions. Ma

arXiv:2608.28671v1 Announce Type: cross Abstract: AI-generated art has sparked debates around potential plagiarism, as these images may closely resemble existing artworks. This research quantifies the

arXiv:2603.00620v3 Announce Type: replace Abstract: Multilingual NLP research increasingly involves hundreds or thousands of languages across different datasets. Managing, discovering, and reporting l

arXiv:2608.31094v1 Announce Type: new Abstract: Patient identity errors can compromise longitudinal medical records, research databases, and downstream clinical decisions. We present a retinal biometr

arXiv:2608.30593v1 Announce Type: new Abstract: In this research, a novel framework is proposed for the SOH estimation, which employs a hybrid deep learning architecture of a concatenation of a Convol

arXiv:2608.30704v1 Announce Type: new Abstract: AI-generated video detection, which aims to distinguish AI-generated videos from real ones, has recently received increasing research attention. To perf

arXiv:2608.29279v1 Announce Type: new Abstract: Deep learning is often criticized for its theoretical research lagging behind practice. To make deep learning easier to understand, the entropy space th

arXiv:2507.22893v3 Announce Type: replace-cross Abstract: Contemporary human-AI interaction research overlooks how AI systems fundamentally reshape human cognition pre-consciously, a critical blind sp

arXiv:2312.10089v2 Announce Type: replace Abstract: Content-based image retrieval (CBIR) systems have emerged as crucial tools in the field of computer vision, allowing for image search based on visua

arXiv:2608.24712v1 Announce Type: cross Abstract: Optimization of hyperparameters is a critical factor to obtain optimal model performance. While existing research has predominantly concentrated on ba