All entries

Amazon Connect Talent is an AI hiring solution built for talent acquisition leaders managing scaled hiring. It delivers AI-led interviews, data-driven assessments, and consistent evaluation, helping r

arXiv:2609.18844v1 Announce Type: new Abstract: Multimodal coding agents are expected to turn visual inputs into usable artifacts, and they act through a harness, the layer of tools, context managemen

arXiv:2609.17653v1 Announce Type: cross Abstract: GUI agents execute long-horizon tasks on dynamic graphical user interfaces, where pop-ups, delayed loads, and relocated widgets routinely invalidate p

arXiv:2609.17817v1 Announce Type: cross Abstract: Thompson's 'Reflections on Trusting Trust' showed that a compiler can be poisoned to reinsert its own backdoor, so that even recompiling clean source

arXiv:2609.18049v1 Announce Type: new Abstract: Model explainability is essential for understanding and trusting machine learning models. Existing explainable AI methods often explain predictions thro

arXiv:2609.17542v1 Announce Type: new Abstract: Large language model services increasingly route each query to one of several models of differing capability, using a cheap estimate of query complexity

arXiv:2609.17654v1 Announce Type: new Abstract: This paper proposes a least squares approach for the training of quadratic neural networks with regularization. The proposed methodology yields a lower

arXiv:2609.18207v1 Announce Type: cross Abstract: Reinforcement learning fine-tuning on top of large, pretrained Vision-Language-Action (VLA) models offers promise for highly reliable robot deployment

arXiv:2609.17537v1 Announce Type: new Abstract: We ask whether relation-type information (e.g., capital-of) and entity-specific information (e.g., France to Paris) become causally active at the final-

arXiv:2609.18291v1 Announce Type: cross Abstract: Use case flows are important elements of use case modeling because they support downstream software engineering activities, including requirements ana

arXiv:2304.03370v3 Announce Type: replace Abstract: The problem of designing learners that provide guarantees that their predictions are provably correct is of increasing importance in machine learnin

arXiv:2609.18396v1 Announce Type: cross Abstract: Virtual sensing, the estimation of hard-to-measure quantities from available sensor measurements, is a critical enabler for control and monitoring in

arXiv:2609.18224v1 Announce Type: cross Abstract: From the manifest of Andre Breton, through the transdisciplinary understanding, we arrive at a post-modern manifest. A talk by Laura De Marco (Harvard

arXiv:2609.17577v1 Announce Type: cross Abstract: We study Langevin diffusion and Langevin Monte Carlo (LMC) when the target distribution changes over time. Under a log-Sobolev inequality (LSI), we de

arXiv:2609.18262v1 Announce Type: new Abstract: Precise retrieval of scientific information is fundamentally constrained by long-tailed concepts and high fact-sensitivity of scientific corpora. These

arXiv:2609.19093v1 Announce Type: cross Abstract: Radiologists follow heterogeneous reporting practices. Two radiologists examining the same image and identifying the same clinical findings might neve

arXiv:2609.17555v1 Announce Type: cross Abstract: Efficient deployment of Deep Neural Networks (DNNs) on edge accelerators requires aggressive model compression while maintaining reliability in fault-

arXiv:2609.18092v1 Announce Type: new Abstract: Global localization with scanning millimeter-wave radar remains challenging because place-recognition descriptors often discard spatial structure needed

arXiv:2609.18708v1 Announce Type: cross Abstract: In reinforcement learning for large language models, Proximal Policy Optimization (PPO) commonly uses a critic to estimate state values and reduce the

arXiv:2609.17644v1 Announce Type: cross Abstract: Domain-specialized language models are widely used for scientific question answering, but stronger general-purpose systems raise a sharper question: w

arXiv:2609.18134v1 Announce Type: cross Abstract: Methodological progress in artificial intelligence (AI) for electronic health records (EHRs) depends on our ability to determine which algorithms work

arXiv:2609.17745v1 Announce Type: cross Abstract: A central goal of autonomous reinforcement learning is continuous policy training without external resets. However, existing paradigms largely depend

arXiv:2609.18656v1 Announce Type: new Abstract: Sign-based methods reduce communication costs in distributed environments, but aggregating local signs can introduce bias when data are heterogeneous. A

arXiv:2609.18545v1 Announce Type: new Abstract: In this paper, we study the detection of an echo chamber in a social network, i.e., the identification of a set of nodes that agree on a topic, while di

arXiv:2609.17985v1 Announce Type: new Abstract: AI agents are usually evaluated by whether they complete a task. In interactive service settings, a successful agent can still frustrate users by asking

arXiv:2609.18442v1 Announce Type: new Abstract: Safe motion planning in automated driving requires anticipating evolving traffic risks and deciding when to revise the current planned trajectory. We in

arXiv:2609.19074v1 Announce Type: cross Abstract: Reinforcement learning (RL) is an exciting concept as well as a remarkable success story worth sharing. However, RL builds on rather complex interacti

arXiv:2609.19104v1 Announce Type: cross Abstract: Factory work is a promising early scenario for embodied AI: assigning repetitive manual jobs to robots has clear economic payoff, and a structured sta

arXiv:2609.17843v1 Announce Type: cross Abstract: Video anomaly detection (VAD) is an actively studied task, having wide applications in typical scenarios such as public surveillance and road traffic

arXiv:2609.17646v1 Announce Type: cross Abstract: This thesis develops robust and efficient AI frameworks for accelerating crystalline materials discovery by addressing both major stages of the materi

arXiv:2609.18304v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly tackle long-horizon tasks through multi-step environment interaction, yet a single erroneous action can a

arXiv:2609.19072v1 Announce Type: new Abstract: Large language models are increasingly used for content moderation, but most evaluations still report aggregate accuracy on individual benchmarks. We in

arXiv:2609.17775v1 Announce Type: new Abstract: Enterprise guideline documents mix narrative text, complex tables, and embedded images, and converting them into structured work artifacts still takes t

arXiv:2609.17788v1 Announce Type: cross Abstract: We present SAiFE_gym, a Python module that provides a collection of simulation environments for studying trading problems in Constant Product Markets

🐙 Sakana Fugu Max is now on Sakana Chat 🐙 Free for all to use. Try it: https://chat.sakana.ai Blog: https://sakana.ai/chat-fugumax/#English 🐡 Media Introducing Fugu Max and Fugu Ultra v2: the next evo

arXiv:2609.17748v1 Announce Type: new Abstract: Deep neural networks that are independently trained to similar performance can be connected by low-loss parametric curves in weight space, a phenomenon

arXiv:2601.11262v2 Announce Type: replace-cross Abstract: Music Cover Retrieval, also known as Version Identification, aims to recognize distinct renditions of the same underlying musical work, a task

arXiv:2609.17639v1 Announce Type: cross Abstract: Modern recommendation systems largely infer user preferences from implicit behaviors such as clicks, watch time, and negative feedback, but these sign

Schmidhuber was building recursive self-improving systems back in 1987. His new post covers four decades of RSI, from meta-evolution and self-modifying policies to the Gödel Machine and modern LLM age

arXiv:2609.19134v1 Announce Type: new Abstract: Scientific code repositories encode decades of human knowledge in executable models, methods, and tools. Yet fragmented toolchains, implicit domain conv

arXiv:2609.18310v1 Announce Type: new Abstract: We introduce Nemotron-SEA-LION-v4.8, a family of Southeast Asian Languages in One Network (SEA-LION) built upon NVIDIA Nemotron 3. The family includes 3

arXiv:2609.18819v1 Announce Type: new Abstract: We propose SEAM, a LiDAR-based lifelong mapping framework. Instead of relying on a single anchor spanning the entire session, SEAM generates evidence ba

arXiv:2609.19090v1 Announce Type: cross Abstract: Can an attacker turn influence over an artificial intelligence (AI) adviser into a harmful quantum error-correction update? We identify an ambiguity i

Choosing the right vector store for your Amazon Bedrock Knowledge Bases RAG application affects performance and cost. This post compares Amazon OpenSearch Service, Amazon Aurora PostgreSQL with pgvect

arXiv:2609.18672v1 Announce Type: new Abstract: An AI assistant that calls tools makes two decisions on every request: which tool to invoke, and whether any available tool applies. In the usual design

arXiv:2609.17545v1 Announce Type: new Abstract: Deep learning models for cervical cytology are almost always evaluated as if every prediction must be acted upon, yet a screening system deployed alongs