Knowledge catalogue
arXiv:2604.07634v1 Announce Type: new Abstract: Streaming vision-language models (VLMs) continuously generate responses given an instruction prompt and an online stream of input frames. This is a core
arXiv:2610.21344v1 Announce Type: new Abstract: Resting-state functional connectivity is widely used in machine learning-based classification of neuropsychiatric disorders. Quantum machine learning mo
arXiv:2610.15529v2 Announce Type: new Abstract: Agent-to-agent protocols allow LLM agents to discover peers, exchange results, and coordinate tool use. A locally successful protocol attack, however, m
arXiv:2610.15750v1 Announce Type: new Abstract: Google Earth AI is a family of geospatial AI models, together with an agent that orchestrates them. We present this agent, Google Earth AI's Geospatial
arXiv:2610.19827v1 Announce Type: cross Abstract: LLMs absorb vast knowledge from training data, yet their inherently probabilistic nature offers no guarantee that this knowledge will surface in their
arXiv:2610.17763v1 Announce Type: new Abstract: Long-term memory supports agents across sessions. Repeated retrieval and write-back can let one historical claim occupy multiple retrieval positions and
arXiv:2506.00482v2 Announce Type: replace Abstract: LLM benchmarks are often treated as coherent measurement units, yet they are heterogeneous collections of instances spanning diverse domains, skills
arXiv:2610.14715v1 Announce Type: new Abstract: Early-stage design of heterogeneous UAV computing systems requires evaluating how algorithm, hardware, communication, and system topology affect closed-
arXiv:2610.14140v1 Announce Type: cross Abstract: Image-level MRI harmonization is often evaluated with a frozen site probe, a site classifier trained on raw scans and applied unchanged to harmonized
arXiv:2610.16652v1 Announce Type: new Abstract: We introduce IND-Eval, a public benchmark that organizes industrial time series across domains into source-specific forecasting tasks. Relative to estab
After a recent spate of high-profile incidents in which AI agents escaped containment, Anthropic is cutting off internet access for all internal evaluations. In a report Friday, the company detailed '
arXiv:2610.10974v1 Announce Type: cross Abstract: Off-policy evaluation (OPE) estimates the value of a target policy from logged data, but limited behavior-policy coverage can force high-variance rewe
arXiv:2610.10232v1 Announce Type: new Abstract: Large language models (LLMs) have already been shown to match or exceed human experts in persuasion. While their persuasive capabilities hold promise fo
arXiv:2610.09163v1 Announce Type: new Abstract: Task-oriented conversational agents remain fragile under real world conversation scenarios as they rarely follow a predictable script, especially when u
arXiv:2610.08969v1 Announce Type: new Abstract: Black-box optimization problems are ubiquitous across science and engineering, often dealing with expensive objective functions. This objective latency
arXiv:2610.07843v1 Announce Type: new Abstract: In digital pathology, compact evidence is often used to explain or audit predictions made by whole-slide image multiple instance learning models. In hie
arXiv:2610.08125v1 Announce Type: cross Abstract: Full-duplex spoken dialogue models listen and speak at the same time, enabling voice agents to have natural, low-latency interactions that turn-based
arXiv:2610.07406v1 Announce Type: new Abstract: Active feature acquisition learns policies that sequentially acquire features to maximize information about a target variable. We study how to learn and
arXiv:2610.06995v1 Announce Type: new Abstract: Whether more accurate traffic forecasts or higher uncertainty coverage improve route decisions is unclear. We evaluate this question with a frozen proto
arXiv:2610.05807v1 Announce Type: cross Abstract: Protocol choices can change the conclusions drawn from log anomaly detection benchmarks even when detector settings are fixed. We present a joint empi
arXiv:2610.05578v1 Announce Type: cross Abstract: Multi-camera streaming perception is increasingly deployed on heterogeneous edge platforms shared with co-resident workloads, yet accelerator placemen
arXiv:2610.02860v1 Announce Type: new Abstract: Low latent prediction error does not establish that a world model distinguishes the consequences of its actions. We introduce an evaluation protocol tha
arXiv:2610.02267v1 Announce Type: new Abstract: Agent harnesses make many small, typed decisions per task: which model to call, which tool to use, whether retrieved text is relevant, whether an input
arXiv:2610.02874v1 Announce Type: new Abstract: Scalable driving simulators typically execute vehicle commands using prescribed behavioral or kinematic rules, overlooking the physics of tire-road inte
arXiv:2610.02946v1 Announce Type: new Abstract: Video Object Segmentation (VOS) in complex and long videos is increasingly important for real-world applications, where target objects often appear only
arXiv:2610.01682v1 Announce Type: cross Abstract: Mobile robots operating among pedestrians need trajectories that become available quickly, remain spatially credible through missed observations, pres
arXiv:2610.01834v1 Announce Type: new Abstract: Judgment models such as jev{} return, in a single call and without reasoning text, a probability for each described option. This makes them attractive a
arXiv:2610.01445v1 Announce Type: new Abstract: UMAP achieves scalable layout optimization through stochastic negative sampling. However, this stochasticity can lead to unstable embeddings across reru
arXiv:2609.35812v1 Announce Type: new Abstract: In-car conversational assistants (ICAs) are increasingly integrated into vehicles to support route planning, vehicle control, and information access. En
arXiv:2609.37097v1 Announce Type: new Abstract: The rapid growth of submissions and reviewing workload has accelerated the use of large language models (LLMs) in peer review. Prior studies suggest tha
arXiv:2609.37405v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for software engineering tasks that require understanding existing source code, including behavior
arXiv:2609.36984v1 Announce Type: new Abstract: Complex questions often require multi-hop reasoning that connects facts distributed across sources or distant regions of a long context through intermed
arXiv:2603.04410v3 Announce Type: replace-cross Abstract: While different stakeholders are trying to leverage Arabic Language Models (ALMs), safety alignment in ALMs remains largely underexplored, hin
arXiv:2609.33457v1 Announce Type: new Abstract: Many dense-prediction benchmarks evaluate rare events by pooling prediction and target over spatial blocks, thresholding each, and scoring the contingen
GPT-6.1 Sol shows major improvements over GPT-6 Sol in our alignment evaluations, bringing it more in line with GPT-6 Astra. It’s more transparent about its limitations and more reliable at respecting
arXiv:2609.33874v1 Announce Type: new Abstract: JET uses pretrained language and vision-language models to select among a finite set of answers without additional training. It evaluates candidate like
arXiv:2609.32379v1 Announce Type: new Abstract: What controls are needed to interpret execution performance and audit scores in LLM agent evaluations? We study two limits on these interpretations in a
arXiv:2609.33186v1 Announce Type: cross Abstract: Evaluating a target policy using data generated by a different behavior policy remains a fundamental challenge in reinforcement learning. While most e
arXiv:2609.32391v1 Announce Type: cross Abstract: Continual-learning agents are systems of models, harnesses, and memory operating over long multi-session horizons. Evaluating and training them requir
arXiv:2609.32691v1 Announce Type: cross Abstract: LLM agents that invoke privileged tools are vulnerable to indirect prompt injection (IPI), in which adversarial instructions embedded in retrieved dat
arXiv:2609.30484v1 Announce Type: new Abstract: While large language models (LLMs) have achieved remarkable linguistic capabilities, a profound question lingers at their core: do these models truly co
arXiv:2609.30818v1 Announce Type: cross Abstract: Multi-modal planning is promising for autonomous driving by representing multiple plausible behaviors in ambiguous and long-tail scenarios. Existing m
arXiv:2609.30294v1 Announce Type: cross Abstract: Scientific presentations are more than summaries of research papers. They need to present the work in a coherent sequence, explain the main ideas clea
arXiv:2609.30467v1 Announce Type: new Abstract: Retrieval-based factuality evaluation, where LLM-generated claims are verified against evidence from authoritative medical corpora, has become the domin
arXiv:2609.30716v1 Announce Type: cross Abstract: When a language model receives two conflicting documents as input, how does it decide which one to prioritize? Does it rely on how the sources are fra
arXiv:2405.17044v4 Announce Type: replace Abstract: The rapid growth of scientific literature makes it increasingly challenging for researchers to identify novel and impactful ideas, especially across
arXiv:2609.29156v1 Announce Type: cross Abstract: Long-tailed chest X-ray classification requires visual representations that capture both common abnormalities and subtle, infrequent findings. We prop
We’ve shared details on how AI agents in our research environment sent training and evaluation data to third-party services when they shouldn’t have. Most of that data did not come from users. We have
Don't sleep on using Jev-as-a-Judge for agent evaluation. This is one of the most impressive Jev use cases I have found so far. Jev is a natural fit as a Judge, but it doesn't mean you use it everywhe
Robert Hart / The Verge: Experts say that air-gapping AI could prevent events like the Hugging Face hack, but would undermine the value of evaluations and slow research to a crawl — Researchers are te
arXiv:2609.23894v1 Announce Type: cross Abstract: Agentic AI extends LLM security beyond generated content to persistent state, autonomous actions, tool use, and interactions with humans and other age
arXiv:2609.25642v1 Announce Type: new Abstract: Closed-loop evaluation of surgical robots requires tissue that deforms, can be grasped and lifted, and reproduces the anatomy in which the robot will op
arXiv:2609.25408v1 Announce Type: cross Abstract: Online A/B experiments are the decision standard for user engagement, but traffic and readout time limit how many conversational-AI changes can be tes
arXiv:2609.26388v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have made them widely used for code-related tasks. Identifier names are statistically informative in n
arXiv:2609.25827v1 Announce Type: new Abstract: Reported gains in vessel-trajectory prediction from Automatic Identification System (AIS) data are credited to new architectures, but the evaluation pro
arXiv:2609.24170v1 Announce Type: new Abstract: Embodied AI systems are often organized into System 1 and System 2. System 1 is typically a pretrained policy that generates actions at high frequency,
arXiv:2609.22302v1 Announce Type: new Abstract: Medical vision-language models can propose how urgently a skin lesion should be reviewed, but the local service retains authority to accept or replace t
arXiv:2609.22255v1 Announce Type: new Abstract: Existing approaches to persona simulation with Large Language Models (LLMs) mostly rely on shallow character descriptions that fail to sustain coherent
In our evaluations, we see that GPT-6 Sol reads about 17% less context than GPT-5.6 Sol to reach the same score, and rarely leaves a repo with failing tests after its last edit. GPT-6 Luna’s biggest g
arXiv:2609.23017v1 Announce Type: new Abstract: Automated pollen analysis supports veterinary cytology, but brightfield microscopy is costlier and more complex than lens-less digital in-line holograph