Knowledge catalogue
arXiv:2609.02688v1 Announce Type: new Abstract: Future-aware representations and world models are increasingly used in proposal-based autonomous-driving planners to improve trajectory selection. Howev
Hot take on OpenAI GPT-6 Astra*, with a challenge to @gdb’s claims about it being AGI toward the end: • Looks to be pretty impressive. Multiple reports suggest it is a genuine advance. • As someone wh
arXiv:2609.02289v1 Announce Type: new Abstract: Detectors trained on closed-set annotations can miss rare moving objects outside the training taxonomy. Automotive radar provides category-independent D
arXiv:2609.02302v1 Announce Type: new Abstract: A core obstacle to alignment evaluation is evaluation awareness: capable models can tell when they are being tested rather than deployed, weakening the
arXiv:2503.00287v3 Announce Type: replace Abstract: Reinforcement learning (RL) has achieved remarkable success in various robotic tasks; however, its deployment in real-world scenarios, particularly
arXiv:2609.02020v1 Announce Type: new Abstract: This study proposes a novel Model Predictive Path Integral (MPPI)-based task-space control framework. The proposed framework explicitly solves rigid-bod
Today we're launching Base Labs, a research lab by Baseten. Our mandate is to make open-source as useful as possible, and our one rule is that we publish without exception, including what fails. Up un
arXiv:2609.00374v1 Announce Type: cross Abstract: Test-time adaptation (TTA) typically assumes that model parameters can be updated at inference time. This assumption is restrictive for inference-only
arXiv:2609.00576v1 Announce Type: new Abstract: Item-sensitivity, defined as whether a model's choice depends on the specific input rather than on its own output prior, is widely reported as evidence
arXiv:2609.00682v1 Announce Type: new Abstract: Intelligent vehicles increasingly support adaptive applications beyond driving themselves, ranging from context-aware ADAS and automated driving to in-c
arXiv:2609.00808v1 Announce Type: cross Abstract: As far-right actors increasingly exploit online platforms to disseminate ideology and mobilize supporters, civil society organizations (CSOs) play a v
arXiv:2606.17506v2 Announce Type: replace Abstract: Evaluations of social bias in LLMs largely focus on whether models generate or imply biased content. However, as LLMs are increasingly used as judge
arXiv:2609.01491v1 Announce Type: cross Abstract: The growing rate at which LLM agents interact with one another raises key questions about language evolution in multi-LLM-agent settings, with implica
arXiv:2609.01339v1 Announce Type: new Abstract: Road traffic noise remains a major environmental challenge, yet most speed management strategies are static and do not respond to short-term variations
Georgia Wells / Wall Street Journal: OpenAI is facing a new round of lawsuits from witnesses and victims of the February mass shooting in a Canadian town; the suspect spent days talking to ChatGPT — N
arXiv:2609.01418v1 Announce Type: cross Abstract: To mitigate the sample complexity of real-world reinforcement learning (RL), a common practice is to first train a policy in a simulator, where sample
arXiv:2609.01470v1 Announce Type: new Abstract: As AI systems are increasingly used to draft radiology reports, reliably evaluating their clinical quality remains a critical challenge. Large language
arXiv:2609.00584v1 Announce Type: new Abstract: Does unrestricted AI access bypass the cognitive effort required for learning, or does it streamline knowledge acquisition? This paper reports on a stud
arXiv:2511.05059v3 Announce Type: replace Abstract: During laparoscopic surgery, smoke generated by tissue cauterization can significantly degrade the visual quality of endoscopic frames, increasing t
arXiv:2512.03994v4 Announce Type: replace Abstract: As organizations increasingly deploy LLMs in sensitive domains such as legal, financial, and medical settings, ensuring alignment with internal orga
arXiv:2609.00038v1 Announce Type: cross Abstract: Outcome-only evaluation is the production default for LLM agents: show a judge the request and the final reply and ask whether it was handled well. Th
arXiv:2608.29347v1 Announce Type: new Abstract: Operators remain essential to Remotely Operated Vehicle (ROV) operation, yet often suffer from low situational awareness and high workload, both of whic
arXiv:2608.30724v1 Announce Type: cross Abstract: LLM agents are increasingly used to run autonomous ML experiments, iterating on target metrics with little human oversight. Prior work has documented
arXiv:2608.30283v1 Announce Type: cross Abstract: Expected-cost constraints can still permit rare, high-cost events. Monte Carlo conditional value at risk (CVaR) gradients can be noisy at high confide
arXiv:2608.29206v1 Announce Type: new Abstract: Bias in human-agent interaction can manifest not only through hostile language but also as benevolent bias, whereby unequal treatment hides behind a war
arXiv:2510.25901v2 Announce Type: replace Abstract: The vulnerability of cyclists, exacerbated by the rising popularity of faster e-bikes, motivates adapting automotive perception technologies for bic
arXiv:2608.31105v1 Announce Type: new Abstract: Users of a deployed language model routinely encounter behaviours that testing almost never surfaces, since deployment puts the model through orders of
arXiv:2608.29000v1 Announce Type: new Abstract: Autonomous vehicles stream high-resolution surround-camera frames into memory before perception runs. This sensor-to-memory path consumes energy when ce
arXiv:2608.28677v1 Announce Type: new Abstract: This paper presents l{CogRun}, a framework that enables safety-critical ground robots to perform cognitively-grounded runtime learning entirely on edge-
arXiv:2502.12527v2 Announce Type: replace Abstract: Text-to-image diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the
arXiv:2608.29118v1 Announce Type: new Abstract: Fine-tuning large language models (LLMs) on narrowly harmful datasets can lead to misalignment broadly, a phenomenon known as emergent misalignment (EM)
arXiv:2608.29978v1 Announce Type: new Abstract: Large language models are increasingly required to generate responses that satisfy multiple competing objectives. Since optimal trade-offs depend on bot
arXiv:2608.28820v1 Announce Type: new Abstract: Computational pathology (CompPath) is transforming medicine by leveraging artificial intelligence (AI) algorithms to support diagnosis, prognosis, and t
arXiv:2608.29108v1 Announce Type: new Abstract: Four-wheel independent steering (4WIS) mobile robots support multiple motion modes, offering high maneuverability in narrow and complex environments. Ho
arXiv:2608.29590v1 Announce Type: new Abstract: We propose a societal bias evaluation method for large vision-language models (LVLMs) in the era of strong safety guardrails. Existing benchmarks rely o
arXiv:2608.30520v1 Announce Type: new Abstract: Automated material handling systems in semiconductor fabs are operated by a material control system (MCS) that must schedule a relay route for every tra
arXiv:2608.30676v1 Announce Type: new Abstract: When medical AI systems hallucinate clinical reasoning, the consequences extend beyond incorrect answers: fabricated justifications that superficially r
arXiv:2608.29136v1 Announce Type: cross Abstract: We ask whether a model protects a user in the same way when that user speaks rather than types. Using a single distress vignette---a physical injury o
arXiv:2502.20325v3 Announce Type: replace-cross Abstract: Multi-rotor aerial autonomous vehicles (MAVs, more widely known as 'drones') have been generating increased interest in recent years due to th
arXiv:2603.19843v2 Announce Type: replace-cross Abstract: The ubiquity of multimedia content is reshaping online information spaces, particularly in social media environments. At the same time, search
arXiv:2608.28728v1 Announce Type: new Abstract: Urban construction governance requires early decisions that connect workplace safety, permitting requirements, and community impact, yet the relevant ev
arXiv:2508.16013v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in politically sensitive contexts, raising concerns about their susceptibility to ideological
arXiv:2608.30874v1 Announce Type: cross Abstract: This paper considers decentralized contingency MPC for multi-agent control under a state-only information pattern, with particular focus on limited se
arXiv:2608.30727v1 Announce Type: cross Abstract: Small-object detection under long-tailed data distributions is a fundamental yet challenging problem in multimedia. Railway Foreign Object Detection (
arXiv:2608.29153v1 Announce Type: new Abstract: Automated radiological report generation can alleviate clinical workloads and eliminate observer variability. However, standard free-text generation mod
arXiv:2608.30050v1 Announce Type: new Abstract: Building a blockchain digital twin largely requires translating domain knowledge and specific system descriptions into a simulator architecture, calibra
arXiv:2608.29516v1 Announce Type: new Abstract: Robotic ultrasound policies operating directly on B-mode images require extensive interaction data, whereas real-robot data collection is costly and saf
arXiv:2608.30748v1 Announce Type: cross Abstract: Existing jailbreak evaluations typically characterize robustness using a single attack success rate (ASR) measured in a default configuration (the van
Depending on who you ask, developer platform Hugging Face was recently attacked by OpenAI - after it lost control of its own AI tools - or by a succession of AI 'civilizations.' Welcome to the linguis
arXiv:2608.30842v1 Announce Type: new Abstract: Humans play a vital role at every stage of AI development, from data collection and curation to model development and evaluation. However, humans often
arXiv:2511.11743v4 Announce Type: replace-cross Abstract: Deploying deep neural networks on resource-constrained devices faces two critical challenges: maintaining accuracy under aggressive quantizati
Whatever you may think about anthropomorphic language, the most immediate “house that is on fire” is the combination of OpenAI’s lax security procedures and the complete lack of appropriate federal st
arXiv:2608.30683v1 Announce Type: new Abstract: Language models are increasingly mediating information access to end users, urging a systematic evaluation of their responses for a fair and reliable in
arXiv:2608.30856v1 Announce Type: new Abstract: Refusals are often treated as face-threatening acts in pragmatics because they can challenge the requester's socially claimed self-image. Large language
arXiv:2608.28063v1 Announce Type: new Abstract: Multi-organ ultrasound classifiers increasingly combine attention, mixture-of-experts routing, uncertainty gating, and evidential deep learning (EDL) ob
arXiv:2505.15450v3 Announce Type: replace Abstract: Text-to-image diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the
arXiv:2608.27726v1 Announce Type: new Abstract: Multi-agent motion planning for high-degree-of-freedom robotics manipulators in shared workspaces remains a fundamental yet challenging problem. Central
arXiv:2608.28052v1 Announce Type: new Abstract: Artificial intelligence has strong potential to support clinical decision-making, yet its adoption in healthcare remains limited due to a lack of trust.
arXiv:2608.27531v1 Announce Type: cross Abstract: The safety of large vision-language models is increasingly stress-tested by multimodal jailbreaks, yet existing attacks remain largely static at the m
arXiv:2608.27989v1 Announce Type: new Abstract: For cooperative perception in the internet of vehicles, this paper proposes a generative adversarial network-based semantic communication framework to a