Towards World Models in Biomedical Research
arXiv:2606.05925v1 Announce Type: new Abstract: A central goal of biomedicine is to understand, predict and ultimately control the dynamic mechanisms by which biological systems respond to perturbatio
Knowledge catalogue
arXiv:2606.05925v1 Announce Type: new Abstract: A central goal of biomedicine is to understand, predict and ultimately control the dynamic mechanisms by which biological systems respond to perturbatio
arXiv:2606.05852v1 Announce Type: cross Abstract: Text-to-speech (TTS) and singing voice synthesis (SVS) both aim to generate human vocal audio from symbolic inputs, but they impose different requirem
arXiv:2606.06207v1 Announce Type: new Abstract: Veterinary pharmacovigilance systems are essential for monitoring adverse drug events (ADEs), yet existing approaches often fail to capture region-speci
Gary Marcus expresses concern about contemporary global instability, suggesting that human greed and desperation pose significant risks to an already precarious historical moment. The post implies tha
arXiv:2606.06356v1 Announce Type: new Abstract: Multimodal generative models produce fluent outputs but remain unreliable when generation must respect structured, domain-specific, or safety-critical k
Whether SpaceX/ Xai is making money on the deals with Google and Anthropic or losing money, they are waving the towel on winning the frontier model race— by arming their competitors rather than themse
Leo Schwartz / The Information: White House AI advisor Sriram Krishnan says he will leave his role at the end of June; sources: Krishnan plans to start a pro-Trump AI policy institution — Sriram Krish
wild thought: will US invest in Anthropic, the alleged supply chain risk? weird if they do. but if they don’t (but do invest in OpenAI) the US government may immensely and immediately increase Anthrop
arXiv:2606.05396v1 Announce Type: cross Abstract: Producing a labeled vulnerable code at scale is a recurring obstacle for learning-based vulnerability detection: mined corpora carry substantial label
arXiv:2606.06272v1 Announce Type: cross Abstract: Generative Flow Networks (GFlowNets) are a framework for sampling structured objects via stochastic trajectories in a directed graph. In this work, we
arXiv:2606.05433v1 Announce Type: new Abstract: Frontier AI governance frameworks increasingly use cumulative training compute as the primary criterion for designating high-impact models, but enforcem
arXiv:2606.06420v1 Announce Type: new Abstract: We present the first Komi-Yazva--Russian parallel corpus together with an explicit evaluation protocol for studying LLM translation in an endangered, ex
arXiv:2512.15792v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have rapidly become indispensable tools for acquiring information and supporting human decision-making. However,
Absofuckinglutely called it. Nationalized stakes are just a bailout by a different name. Here we are seventeen months later, and the fleece the taxpayer game is on. The countdown until we are told tha
arXiv:2606.05906v1 Announce Type: new Abstract: Text-to-SQL maps natural language questions to executable SQL queries. Modern databases often contain large and complex schemas, making schema linking a
arXiv:2606.06186v1 Announce Type: new Abstract: Vision-Language Models (VLMs), such as CLIP, have shown strong zero-shot generalization but remain highly vulnerable to adversarial perturbations, posin
arXiv:2602.12124v2 Announce Type: replace-cross Abstract: While most AI alignment research focuses on preventing models from generating explicitly harmful content, a more subtle risk arises from capab
“America won’t win the AI race if we beat China but end up with a CCP-style social credit system in the U.S. — and that is the danger as the government becomes more deeply involved in AI development a
arXiv:2606.05864v1 Announce Type: new Abstract: We investigate the extent to which the language processing of LLMs resembles human cognitive processes, focusing on a human cognitive bias called the ex
arXiv:2606.06308v1 Announce Type: new Abstract: Triaxial MEMS accelerometers are widely used for inertial sensing, navigation, and sensor fusion, but existing calibration methods often rely on costly
arXiv:2606.05588v1 Announce Type: new Abstract: Imitation-learning policies inherit the quality of the demonstrations they are trained on, and a growing set of curation metrics promise to score and fi
arXiv:2606.05985v1 Announce Type: new Abstract: Multicultural multi-agent systems are increasingly deployed in globally diverse settings, where different agents are grounded in different cultural back
arXiv:2602.12628v4 Announce Type: replace Abstract: Simulation offers a scalable and low-cost way to enrich vision-language-action (VLA) training, reducing reliance on expensive real-robot demonstrati
arXiv:2606.05711v1 Announce Type: new Abstract: Multi-agent systems built on large language models (LLMs) have become a prevailing paradigm for tackling complex reasoning, planning, and tool-use tasks
arXiv:2606.05523v1 Announce Type: new Abstract: Despite advances in safety alignment, prompt-rewriting attacks such as persona modulation, fictional framing and persuasion-based reformulation, can byp
arXiv:2606.06349v1 Announce Type: new Abstract: Several of the world's languages are still under-resourced in terms of Natural Language Processing (NLP) tools. This is mostly due to the lack of high-q
arXiv:2606.05753v1 Announce Type: new Abstract: Latent visual reasoning (LVR) inserts supervised latent tokens between perception and answer generation in vision-language models (VLMs). The field uses
arXiv:2606.05699v1 Announce Type: new Abstract: Bimanual dexterous tool use remains challenging for robots due to high-dimensional hand configurations and complex hand-tool-object dynamics and contact
arXiv:2606.05645v1 Announce Type: new Abstract: Autonomous driving requires reasoning about how ego actions shape the evolution of the surrounding world. However, most end-to-end methods rely on direc
arXiv:2606.05455v1 Announce Type: new Abstract: The missing-modality problem poses a significant challenge in image-tabular multimodal learning across a wide range of multimedia applications, includin
arXiv:2606.05290v1 Announce Type: new Abstract: Recent progress in generative modeling has made safety control a central challenge, yet existing approaches remain largely model-specific, requiring ret
arXiv:2606.05185v1 Announce Type: cross Abstract: Mass gathering events are associated with critical safety incidents caused by insufficient crowd monitoring and inadequate emergency response coordina
arXiv:2602.10106v2 Announce Type: replace Abstract: Human demonstrations offer rich environmental diversity and scale naturally, making them an appealing alternative to robot teleoperation. While this
arXiv:2606.05894v1 Announce Type: new Abstract: Long-horizon agents can archive large histories, but future answers still incur retrieval, rereading, and context costs. When retained memory misses ans
arXiv:2606.06370v1 Announce Type: new Abstract: Wearable exoskeletons can augment human phys ical capabilities during complex activities. However, ensuring adaptation across diverse tasks while guaran
arXiv:2606.05936v1 Announce Type: new Abstract: Modern language models rely on pretraining filters to remove undesirable content from training corpora and inference-time guardrails to suppress undesir
arXiv:2512.21430v2 Announce Type: replace Abstract: Visuomotor policies based on generative such as diffusion and flow-matching have shown strong performance for robotics applications but degrade unde
Finally, a commencement speaker who calls bullshit. Great oped by @mollyjongfast on “billionaire brain”, and why young people have a right to boo what the AI industry has become. I wrote about the com
arXiv:2606.06461v1 Announce Type: new Abstract: Leveraging prior knowledge from pretrained policies, foundation models, or human operators offers an efficient alternative to learning robot skills from
arXiv:2606.05468v1 Announce Type: new Abstract: Post-training Vision-Language-Action (VLA) models into policies that can be reliably deployed on real robots remains a major bottleneck. SFT and DAgger
arXiv:2606.05857v1 Announce Type: new Abstract: Handling toxic retrieval in text-to-audio systems is challenging due to contextual dependencies. Existing strategies (e.g., rephrasing, summarization) r
Funny how so many people read Anthropic is calling for a pause when they did NOT actually call for a pause. Read what they said, carefully. They want it both ways. They *don’t* actually want a pause -
arXiv:2606.05883v1 Announce Type: new Abstract: Dataset condensation aims to construct compact datasets from real data via synthesis or selection. However, existing approaches are ill-suited for diffu
arXiv:2606.05889v1 Announce Type: cross Abstract: We propose GLASS, a framework for composable acoustic style control in zero-shot autoregressive text-to-speech (TTS) that learns controls from post-ge
arXiv:2602.05056v2 Announce Type: replace-cross Abstract: Online scams increasingly leverage fluent and context-aware social engineering strategies, creating growing demand for AI systems that explain
arXiv:2606.06493v1 Announce Type: new Abstract: For a humanoid robot to be deployed in the real world, the choice of command space (i.e., the interface between task planning and whole-body control) is
arXiv:2602.16705v3 Announce Type: replace-cross Abstract: Visual loco-manipulation of arbitrary in-the-wild objects requires accurate end-effector (EE) control and a generalizable understanding of the
arXiv:2606.06464v1 Announce Type: new Abstract: A long-standing finding in the causal learning literature is that adults struggle to identify conjunctive causal rules, where an effect requires the sim
arXiv:2407.10486v3 Announce Type: replace-cross Abstract: Query-focused summarization (QFS) aims to produce summaries that answer particular questions of interest, enabling greater user control and pe
arXiv:2606.05849v1 Announce Type: cross Abstract: Metasurfaces enable precise manipulation of electromagnetic waves for applications such as beam steering, sensing, and stealth technology. However, in
arXiv:2606.05248v1 Announce Type: new Abstract: Inverting a robotic task requires more than reversing symbolic state transitions or rewinding motor trajectories. In robot manipulation tasks, symbolic
arXiv:2507.06219v2 Announce Type: replace Abstract: Data scaling has driven remarkable success in foundation models for Natural Language Processing (NLP) and Computer Vision (CV), yet the principles o
Yoshua Bengio appeared as a guest on 'The Most Interesting Thing in AI' podcast hosted by N.X. Thompson, where he discussed various topics related to artificial intelligence. The appearance was shared
⚠️ Keep your eye on the ball, and don’t panic over Anthropic’s new blog. Here’s why: Anthropic is trying to strike terror into everyone’s hearts – “full recursive self-improvement also might increase
arXiv:2606.06049v1 Announce Type: new Abstract: Intra-vehicular robots in spacecraft help reduce astronaut workload and improve mission efficiency. Recent research focuses on using deep learning metho
arXiv:2606.05873v1 Announce Type: cross Abstract: Humanoid robots hold great promise for operating in human-centered environments, yet ladder climbing remains one of the most challenging tasks due to
arXiv:2606.05937v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used, including in political applications, but their political fairness has been little studied. We assess
arXiv:2606.06447v1 Announce Type: new Abstract: Large language models often improve reasoning by generating explicit chain-of-thought (CoT), demonstrating the importance of intermediate computation. H
arXiv:2606.05952v1 Announce Type: new Abstract: In this work, we propose an agentic gamification framework for hazard-informed learning of robot safety policies through synthetic scenarios. We model s
arXiv:2606.06076v1 Announce Type: cross Abstract: While vision-language models excel at general multimodal understanding, they still struggle with visual spatial planning. We attribute this to a perce