Knowledge catalogue
arXiv:2609.17479v1 Announce Type: cross Abstract: Despite the rapid uptake of black-box object detectors in marine mammal research and monitoring, explainability techniques are rarely integrated into
arXiv:2609.17043v1 Announce Type: cross Abstract: Multi-hop question answering requires combining information from multiple documents to answer complex questions. These systems have grown increasingly
arXiv:2609.16661v1 Announce Type: new Abstract: Automated depression screening from clinical interviews requires attribution of utterances to the clinician or patient. We evaluate two datasets: DAIC-W
arXiv:2609.16686v1 Announce Type: cross Abstract: Estimating deformable object states remains a fundamental challenge in robotics and simulation. We propose a novel factor graph-based framework for pr
arXiv:2609.16283v1 Announce Type: new Abstract: exttt{URANIA} provides end-to-end differential privacy (DP) for summaries of data-dependent clusters. However, its cluster--keyword release does not dir
arXiv:2609.16062v1 Announce Type: cross Abstract: The studying of opinion dynamics and its propagation within social networks is crucial for addressing a wide range of challenges, including political
arXiv:2601.18493v2 Announce Type: replace Abstract: Vision--language models (VLMs) show promise for disaster-response remote sensing, but existing benchmarks mainly emphasize scene-level or damage-cen
arXiv:2609.16907v1 Announce Type: cross Abstract: AI companions can provide meaningful relationships, yet these relationships remain vulnerable to platform-initiated changes. We study AI companion dis
arXiv:2609.17484v1 Announce Type: new Abstract: This study asks whether training-time motion-prior regularization can improve insertion success when a diffusion policy is learned from only 15 demonstr
arXiv:2609.16091v1 Announce Type: new Abstract: Tabular foundation models deliver strong zero-training predictive performance via in-context learning, but their high inference latency makes them impra
arXiv:2609.17029v1 Announce Type: cross Abstract: Traditional energy forecasting solutions rely on task-specific supervision and energy asset representations, limiting transferability and the ability
arXiv:2609.16617v1 Announce Type: new Abstract: KV-cache eviction perturbs the conditional token distributions governing autoregressive generation. We investigate how first-divergence timing and subse
arXiv:2609.16589v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly handle complex subjective tasks, aligning their intentions and behaviors with human values has become a cri
arXiv:2512.23650v3 Announce Type: replace Abstract: Humans intuitively move to sound, but current humanoid robots lack expressive improvisational capabilities, confined to predefined motions or sparse
arXiv:2509.12626v4 Announce Type: replace-cross Abstract: Aligning agentic AI with user intent is critical for delegating complex, socially embedded tasks, yet user preferences are often implicit, evo
arXiv:2609.16288v1 Announce Type: new Abstract: The North Pacific Subtropical Gyre (NPSG) is a major accumulation zone for floating plastic debris, resulting from basin-scale convergent ocean circulat
arXiv:2609.17247v1 Announce Type: new Abstract: An agentic AI driver-assistance framework that integrates perception, compliance reasoning, vehicle-state interpretation, and safety arbitration into a
arXiv:2609.16058v1 Announce Type: cross Abstract: Red-light violations and harsh braking at signalized intersections are major contributors to traffic accidents. This paper analyzes and predicts human
arXiv:2512.01782v4 Announce Type: replace-cross Abstract: Randomized Smoothing (RS) is a prominent technique for certifying the robustness of neural networks against adversarial perturbations. With RS
arXiv:2609.16450v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a promising parallel decoding paradigm as an alternative to autoregressive generation through iterative
arXiv:2609.17226v1 Announce Type: cross Abstract: An agent that learns from rewards has to trust whatever reports those rewards. When the reports suddenly change, either the world changed or the repor
arXiv:2609.16358v1 Announce Type: cross Abstract: Renewable energy systems and electrified transport have found widespread adoption in recent years. The integration of these non-linear loads, dominate
arXiv:2609.17360v1 Announce Type: new Abstract: Full-duplex spoken dialogue systems must distinguish interruptions that require yielding the floor from backchannels that permit continued speaking. Exi
arXiv:2609.17241v1 Announce Type: new Abstract: While draft-model-free speculative decoding offers a promising path to efficient LLM inference, it is frequently constrained by stale draft candidates a
Echoes of OpenAI renaming the Codex desktop app to 'ChatGPT' here - everyone's racing to establish themselves as a general agent now Claude Cowork and Chat are now one Claude, starting today. The most
arXiv:2609.16635v1 Announce Type: new Abstract: Computer-use agents increasingly operate browsers, software, and desktop applications via CLI or API portals, but graphical user interface (GUI) still p
arXiv:2609.16690v1 Announce Type: new Abstract: Reducing radiation exposure in Positron Emission Tomography (PET) is important for patient safety; however, ultra-low-dose imaging suffers from severe n
arXiv:2609.16070v1 Announce Type: cross Abstract: Generative recommendation reformulates item prediction as semantic identifier generation, yet episodic content introduces a fundamentally different se
arXiv:2609.16312v1 Announce Type: cross Abstract: One-to-many machine translation (MT) is computationally expensive for autoregressive (AR) systems, which suffer from linear latency scaling with both
arXiv:2609.16689v1 Announce Type: new Abstract: Large-scale vision-language models (VLM) such as CLIP enable strong open-vocabulary reasoning, yet deploying these capabilities on resource-constrained
arXiv:2609.16255v1 Announce Type: cross Abstract: We present an efficient method to distill reasoning capabilities into compact video-language models (VLMs) for video question answering (VideoQA). Our
arXiv:2609.16572v1 Announce Type: cross Abstract: Text-to-image diffusion models often use a fixed number of denoising steps, balancing time costs and image quality. However, the optimal number of ste
arXiv:2609.16610v1 Announce Type: new Abstract: Zero-shot waypoint navigation requires vision-language models to select, from the current first-person observation, a sequence of spatial actions that i
AI factories are the infrastructure of the intelligence era. Scaling them responsibly will depend as much on innovation across the grid as inside the data center. Today, Emerald AI, Google and NVIDIA
arXiv:2609.16011v1 Announce Type: cross Abstract: Embodied conversational agents require synchronized full-body motion (body gestures and facial expressions) that aligns with speech and emotional stat
arXiv:2609.17499v1 Announce Type: cross Abstract: Uncertainty estimation for Vision-Language-Navigation (VLN) models is a critical task since it can help identify ambiguous and unreliable predictions,
arXiv:2609.17193v1 Announce Type: new Abstract: Large language model (LLM)-powered agentic AI services increasingly demand low-latency inference, motivating the deployment of LLMs across distributed e
arXiv:2609.17398v1 Announce Type: new Abstract: This paper addresses the challenge of making complex healthcare information more accessible through automated Plain Language Adaptation (PLA). PLA aims
arXiv:2607.27245v2 Announce Type: replace-cross Abstract: Modern policing faces a 'visibility paradox' where law enforcement agencies possess petabytes of Body-Worn Camera (BWC) footage that remains l
arXiv:2601.06834v2 Announce Type: replace Abstract: Low-resolution image representation can be regarded as a special form of sparse representation that retains only low-frequency information while dis
arXiv:2603.13478v2 Announce Type: replace-cross Abstract: In a spiking neural network, is it enough for each neuron to spike at most once? In recent work, approximation bounds for spiking neural netwo
arXiv:2609.17292v1 Announce Type: new Abstract: Control barrier functions for input-constrained systems place the admissible input set inside the definition of the safe set, yet the resulting barrier
arXiv:2609.16926v1 Announce Type: new Abstract: Phenotyping an agricultural crop is crucial for studying its entire life cycle, as it provides vital insights to improve yield and, ultimately, food pro
arXiv:2609.16093v1 Announce Type: new Abstract: A shopping conversation has many routes to the same cart, and a task-success rate reduces all of them to one score. We build a deterministic and reprodu
arXiv:2609.17439v1 Announce Type: cross Abstract: Reliable quantum engineering is essential for turning quantum phenomena into practical technologies. As quantum platforms grow in scale and complexity
arXiv:2609.17134v1 Announce Type: new Abstract: Neuromorphic vision systems operate under strict constraints on bandwidth, memory, and energy, particularly at the edge, motivating early mechanisms for
arXiv:2609.17189v1 Announce Type: new Abstract: 3D hand mesh reconstruction is a challenging yet essential task for downstream applications, including human-robot interaction and AR/VR. Although conve
arXiv:2408.14575v5 Announce Type: replace Abstract: EVINCE (Entropy and Variation IN Conditional Exchanges) is a novel framework for optimizing multi-LLM dialogues using conditional statistics and inf
arXiv:2609.17081v1 Announce Type: new Abstract: Grounded language-model systems are often evaluated by final answer accuracy, yet a correct answer can be unsupported, drawn from the wrong source, or p
arXiv:2609.08171v2 Announce Type: replace Abstract: Low-latency simultaneous speech-to-speech translation must keep pace with ongoing speech while preserving key information. To meet these demands, sy
arXiv:2507.01927v3 Announce Type: replace Abstract: While CNNs and ViTs dominate vision architectures, all-MLP models offer a structurally simpler alternative whose patch-independent processing is nat
Enterprise artificial intelligence services startup Hang Ten Systems Inc. today announced it has raised 53 million in a second seed round, less than three months after announcing its first. Hang Ten p
arXiv:2609.17384v1 Announce Type: new Abstract: Robot teams that learn a common environment model exchange belief summaries and plan by the expected information gain of their actions. Under conjugate
Excited to announce that the Korean translation of 'Deep Learning with Python (3rd Edition)' by @fchollet and @mattdangerw is published! 🚀 Updated for Keras 3, TensorFlow, PyTorch, JAX, and Generative
arXiv:2609.16822v1 Announce Type: new Abstract: This study covers foundational concepts for enhancing plan-execution flexibility, including partial-order planning, the producer-consumer-threat formali
arXiv:2511.20186v2 Announce Type: replace Abstract: Foundation video generation models such as WAN 2.2 exhibit strong text- and image-conditioned synthesis abilities but remain constrained to the same
arXiv:2503.16286v2 Announce Type: replace Abstract: Dementia affects over 55 million people worldwide, projected to reach 139 million by 2050, with Alzheimer's disease (AD) accounting for 60-70% of ca
arXiv:2609.17257v1 Announce Type: new Abstract: Semantic occupancy prediction gives an embodied agent a voxel-level account of where space is free, occupied, and semantically meaningful. In RGB-D pipe
arXiv:2602.05718v2 Announce Type: replace Abstract: Point-supervised Temporal Action Localization (PTAL) adopts a lightly frame-annotated paradigm (extit{i.e.}, labeling only a single frame per action
arXiv:2609.17291v1 Announce Type: new Abstract: The quest for new materials increasingly relies on predictive models and comprehensive simulations that span scales from atomic to macroscopic levels. H