Search: “evaluation”

arXiv:2605.11814v2 Announce Type: replace Abstract: The large-scale deployment of personalized healthcare agents demands memory mechanisms that are exceptionally precise, safe, and capable of long-ter

arXiv:2602.00811v2 Announce Type: replace Abstract: Current Multimodal Affective Computing (MAC) systems heavily rely on the completeness of multiple modalities to accurately understand human's affect

arXiv:2610.11723v1 Announce Type: new Abstract: Multiplayer world models must ensure that independently controlled views remain consistent with one shared and persistent world. We introduce MultiWorld

arXiv:2610.11631v1 Announce Type: cross Abstract: Deploying intelligent robotic systems that interact with humans through gestures requires neural networks capable of recognizing diverse temporal patt

arXiv:2603.07980v2 Announce Type: replace-cross Abstract: As language models (LMs) evolve from chat assistants to long-horizon agents capable of multi-step reasoning and tool use, existing benchmarks

arXiv:2610.12419v1 Announce Type: new Abstract: Single-image, multi-image, and video deep research require different visual operations but share a workflow of visual grounding, external retrieval, and

arXiv:2610.12375v1 Announce Type: new Abstract: Agents are deployed in applications from trip planners and stock trading to IT incident triage. In most cases, LLM agents work autonomously with minimal

arXiv:2602.19661v3 Announce Type: replace Abstract: Temporal information in structured electronic health records (EHRs) is often lost in sparse one-hot or count-based representations, while sequence m

arXiv:2610.12123v1 Announce Type: new Abstract: Generating a plausible robot action does not establish that current observations justify its execution. Motivated by exploratory observations of high-co

arXiv:2610.11423v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student model by aligning its policy with a teacher model on trajectories generated by the student model itself. T

arXiv:2610.10909v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) threaten the privacy of machine learning (ML) training data by determining whether a sample was used to train a ta

arXiv:2610.10625v1 Announce Type: cross Abstract: Looped Language Models (LoopLMs) provide a parameter efficient approach to scaling model capabilities through repeated use of shared parameters across

arXiv:2610.11583v1 Announce Type: cross Abstract: End-to-end autonomous driving demands trajectory planners that are both highly accurate and cheap enough for edge deployment. State-of-the-art artific

arXiv:2610.10703v1 Announce Type: new Abstract: Eyeglass reflection removal is important across smartphone imaging, video conferencing, and other face-centric visual applications. The task is challeng

arXiv:2610.11196v1 Announce Type: cross Abstract: Large audio-language models (LALMs) exploit multimodal evidence, yet task-irrelevant audio can alter text-reasoning decisions when listening is unnece

arXiv:2610.10857v1 Announce Type: new Abstract: Behavior cloning (BC) in non-Markovian environments is a challenging problem because policies have to reason over contextual information over long horiz

arXiv:2610.11825v1 Announce Type: new Abstract: Detecting intra-operative speech impairment during awake craniotomy is essential for preserving language function. However, automated detection remains

arXiv:2610.11296v1 Announce Type: new Abstract: Implicit Neural Representations (INRs) have emerged as a compelling paradigm for modeling multidimensional signals by mapping continuous coordinates to

arXiv:2610.10889v1 Announce Type: new Abstract: Vision-Language (VL) reasoning requires a model to both extract relevant and accurate information from an image (visual reasoning, VR), and to infer the

arXiv:2610.12201v1 Announce Type: cross Abstract: Full-duplex speech models can listen and speak simultaneously, enabling natural interaction, but become increasingly difficult to control as the conve

arXiv:2610.12216v1 Announce Type: new Abstract: This paper presents semi-automatic stride-independent patching (SSP) as an alternative to automatic stride-dependent patching techniques. SSP uses user

Super interesting NVIDIA paper on choosing base models for coding agents. It's actually a clever way to rank base checkpoints by how well each one is likely to do as a coding agent after post-training

arXiv:2610.12126v1 Announce Type: cross Abstract: General-purpose service robots need navigation systems that can handle diverse human requests in unfamiliar environments, combining task generality wi

arXiv:2604.00050v3 Announce Type: replace-cross Abstract: Federated Learning (FL) has emerged as a promising technique for training language models on distributed and private datasets of diverse tasks

arXiv:2610.11333v1 Announce Type: new Abstract: AI services incur inference costs during execution, while revenue may arrive later. Changing API prices, limited upfront capital, and service failures c

arXiv:2610.12172v1 Announce Type: cross Abstract: Learning how actions change scene geometry can provide complementary supervision for goal-directed manipulation. We introduce Spatial Language Modelin

arXiv:2610.12114v1 Announce Type: new Abstract: Knowledge distillation (KD) transfers knowledge from stronger Teacher models to weaker Student models, but most methods require training the Student par

arXiv:2610.12229v1 Announce Type: cross Abstract: In text-guided image editing, describing the desired change is often straightforward, but identifying the intended object or region can be cumbersome,

arXiv:2610.12403v1 Announce Type: cross Abstract: Skill-augmented agents improve sample efficiency by distilling successful trajectories into reusable strategies. Yet most existing approaches remain t

arXiv:2610.11754v1 Announce Type: new Abstract: Some defects in an AI-generated study can be identified from its artifacts; others require knowledge of what was approved before execution. We propose s

arXiv:2610.11188v1 Announce Type: new Abstract: Persistent memory can improve personalization in LLM agents but can also induce sycophancy and cross-domain leakage. We distinguish two governance decis

arXiv:2610.10932v1 Announce Type: new Abstract: Offline goal-conditioned reinforcement learning (GCRL) has produced a diverse set of goal-reaching algorithms, yet no single algorithm performs best acr

arXiv:2610.09891v1 Announce Type: cross Abstract: Human-Robot Collaboration (HRC) can facilitate mass customisation in Industry 4.0, with Reinforcement Learning from Human Feedback (RLHF) representing

arXiv:2610.09302v1 Announce Type: new Abstract: Safe navigation in dynamic environments requires robots to plan under obstacle predictions whose errors are uncertain, non-stationary, and can induce ra

arXiv:2610.08875v1 Announce Type: cross Abstract: Agent Skills package procedural guidance and resources for reuse, but a relevant Skill does not necessarily improve task performance. Existing studies

arXiv:2610.09096v1 Announce Type: new Abstract: While established literature underscores the pivotal role of preprocessing in forecasting accuracy, this stage remains largely overlooked in current res

arXiv:2610.09052v1 Announce Type: new Abstract: Continuous cardiac monitoring outside clinical settings requires signals that are both informative and practical to collect during daily life. Electroca

arXiv:2610.09207v1 Announce Type: new Abstract: Belief-space planners with separately designed or off-the-shelf estimators may have access to state-relevant information the estimator does not observe.

arXiv:2610.10163v1 Announce Type: new Abstract: Linking people's appearance and actions to character identities is essential for understanding video narratives. We present a framework for identity-awa

arXiv:2610.09800v1 Announce Type: new Abstract: Surgical video generation holds substantial potential for surgical education, simulation, and data augmentation, yet generating surgical videos with rea

arXiv:2610.08840v1 Announce Type: new Abstract: Large language models (LLMs) often abandon a correct answer, or endorse a user's position, once the user pushes back. This behavior, called sycophancy,

arXiv:2603.13357v2 Announce Type: replace Abstract: Bi-CamoDiffusion is introduced, an evolution of the CamoDiffusion framework for camouflaged object detection. It integrates edge priors into early-s

arXiv:2610.09873v1 Announce Type: new Abstract: Binary Neural Networks (BNNs) enable efficient deep learning deployment on resource constrained devices with weights and activations compressed to one b

Vultr demonstrated its composable cloud platform at the Agent Arena Hackathon in San Francisco by partnering with Cerebral Valley to build production‑ready enterprise agentic AI systems using Serverle

arXiv:2610.09127v1 Announce Type: cross Abstract: Reconstructing an editable CAD model from a 3D shape remains a challenging engineering task. Existing methods can propose CAD operations, but no singl

arXiv:2610.09552v1 Announce Type: cross Abstract: Watermarking enables language model providers to identify text generated by their models. However, its desired properties can conflict (ie~stronger wa