Knowledge catalogue
arXiv:2607.21255v1 Announce Type: cross Abstract: Slang is a central component of everyday language, reflecting linguistic creativity, social identity, and cultural change, yet its dy- namic and non-s
arXiv:2607.21326v1 Announce Type: new Abstract: Rectified-flow-based diffusion transformers, particularly FLUX, have demonstrated outstanding performance in high-quality image generation. However, ach
arXiv:2607.20691v1 Announce Type: cross Abstract: Concept Bottleneck Models provide interpretable-by-design predictions by mediating diagnosis through human-understandable concepts, but in medical ima
arXiv:2607.20587v1 Announce Type: cross Abstract: Modern power systems increasingly require probabilistic forecasts amid interacting uncertainties from renewable intermittency, flexible demand, market
Statistics of week: “More Americans pay for sports betting apps (5%) than pay for AI… 37% of consumers say none of AI's uses are helpful. … 2.2% penetration nearly four years after ChatGPT launched. N
Stay hungry, stay foolish. Absolute legend For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by ever
arXiv:2607.21239v1 Announce Type: new Abstract: Polarization cues benefit applications such as material detection and de-reflection, yet acquiring them typically requires dedicated hardware. This moti
arXiv:2512.17951v3 Announce Type: replace Abstract: Recent progress in flow-based generative models and reinforcement learning (RL) has improved text-image alignment and visual quality. However, curre
arXiv:2607.20787v1 Announce Type: cross Abstract: For two decades, the standard remedy for class-imbalanced learning has been to fabricate synthetic minority examples, and the standard evidence of the
arXiv:2607.20447v1 Announce Type: new Abstract: This paper describes our system for the EEUCA 2026 Shared Task on toxicity classification in gaming chat. We implement a three-stage pipeline combining
arXiv:2607.21273v1 Announce Type: new Abstract: Dense per-step supervision is an appealing remedy for sparse-reward, long-horizon LLM agents: reward the agent for predicting its next observation, and
The knowledge that makes AI useful is diffused. It lives with scientists, engineers, clinicians, firms. For AI to benefit from distributed knowledge, it must itself be distributed. Agree with Jensen t
arXiv:2607.20449v1 Announce Type: cross Abstract: LLMs are trained predominantly on human-authored text, yet the structural and narrative conventions embedded in that text are rarely examined as a sou
This has my full support. Jensen is right. For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by ever
arXiv:2501.19337v5 Announce Type: replace Abstract: A name alone measurably reshapes a language model's next-token distribution before a single token is sampled. We measure full-vocabulary Shannon ent
arXiv:2607.21325v1 Announce Type: cross Abstract: Autonomous AI agents increasingly execute actions, invoke tools, and operate on protected resources with limited human oversight. Existing authenticat
arXiv:2607.20887v1 Announce Type: cross Abstract: Model merging combines independently trained or fine-tuned models, but pairwise alignability does not imply globally consistent alignment. We formulat
arXiv:2607.21546v1 Announce Type: new Abstract: Multimodal based approaches often outperform single modality approaches in downstream tasks as the different modalities provide complementary informatio
arXiv:2512.12413v2 Announce Type: replace Abstract: Generative AI tools are increasingly embedded in everyday work and learning, yet their fluency, opacity, and propensity to hallucinate mean that use
arXiv:2607.20912v1 Announce Type: new Abstract: Learning-based manipulation policies usually predict robot actions from sensory observations and leave their execution to a separate low-level controlle
arXiv:2607.21151v1 Announce Type: new Abstract: As Video Large Language Models are increasingly deployed in real-world applications, ensuring their safety alignment has become critical. Counterintuiti
arXiv:2512.19178v2 Announce Type: replace-cross Abstract: Bridging the gap between natural language commands and autonomous execution in unstructured environments remains an open challenge for robotic
Was great to talk about this timely and alarming news, thanks for having me on! . @NPCollapse, executive director at ControlAI, joins 'On Balance' to discuss the dangers of artificial intelligence aft
We are pleased to announce that @GaryMarcus, Professor Emeritus at New York University, will speak at the 19th Annual AGI Conference (July 27–30, 2026). Professor Marcus is a leading voice in artifici
Welcome @jensenhuang 💚 The future of AI leadership needs both frontier closed models and frontier open models. For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will
https://bfl.ai/blog/flux-3 “Over the next few weeks and months, we will make the following capabilities available, each after an early access phase for ensuring smooth rollout, collecting feedback and
arXiv:2602.12338v2 Announce Type: replace Abstract: Token Communications (TokenCom) has recently emerged as an effective new paradigm, where tokens are the unified units of multimodal communications a
arXiv:2607.20495v1 Announce Type: new Abstract: Multi-agent systems decompose complex tasks into directed acyclic graphs (DAGs) of specialized agent executions, creating natural opportunities for cach
arXiv:2607.21550v1 Announce Type: new Abstract: While large audio-language models have achieved remarkable progress in auditory perception, they still lag behind text-based large language models in de
arXiv:2607.19954v1 Announce Type: new Abstract: Detecting media bias automatically is difficult because biased framing is often subtle, yet in domains such as news analysis, accurate predictions alone
arXiv:2602.04081v2 Announce Type: replace Abstract: Research has repeatedly demonstrated that intermediate hidden states extracted from large language models and speech audio models predict measured b
arXiv:2607.19190v2 Announce Type: replace-cross Abstract: Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a str
arXiv:2607.19768v1 Announce Type: new Abstract: Very Large Scale Integration (VLSI) global routing is an NP-hard combinatorial optimization problem requiring signal net assignment across capacity-cons
arXiv:2406.07746v4 Announce Type: replace-cross Abstract: We propose a computationally efficient algorithm that achieves anytime regret of order O(sqrt{t}), with explicit dependence on the system dime
arXiv:2607.20127v1 Announce Type: new Abstract: The aim of this paper is twofold. First, it investigates whether newer generative models are getting better at pastiching contemporary artworks. Second,
In this post, we explain how Amazon Bedrock Guardrails can be configured for code generation workflows with coding assistants to overcome these constraints. With these best practices, you can build an
arXiv:2511.05865v3 Announce Type: replace-cross Abstract: Recent advancements in large-scale generative models have enabled the creation of high-quality images and videos, but have also raised signifi
arXiv:2607.19827v1 Announce Type: new Abstract: Ensuring safety in Physical AI systems operating in real-world environments is a critical challenge, particularly in hospital wards where vulnerable pat
arXiv:2607.20083v1 Announce Type: cross Abstract: Post-training with evaluator feedback on policy-induced samples serves as a major mechanism for improving large language models. As policies improve,
arXiv:2607.19194v2 Announce Type: cross Abstract: High-level planning for autonomous driving is a knowledge-intensive engineering decision task that requires accurate scene understanding, timely infer
arXiv:2607.18713v1 Announce Type: cross Abstract: Vision-based heading prediction is useful for UAV--UGV cooperation, but accurate prediction alone does not guarantee that every predicted heading shou
arXiv:2607.19708v1 Announce Type: new Abstract: Fully actuated unmanned aerial vehicles (UAVs) are usually certified through rank conditions on a control-allocation matrix or through free-flight track
arXiv:2506.04122v4 Announce Type: replace Abstract: Open-loop performance evaluation of 3D multi-object tracking in autonomous driving requires matching criteria that effectively penalize translationa
arXiv:2607.19046v1 Announce Type: new Abstract: On-policy Distillation (OPD) supervises a student model on trajectories sampled from its own policy by minimizing the divergence between the output dist
.@ControlAI is proud to endorse Reps. Lieu and Moran’s AI Kill Switch Act! This is a common sense safeguard giving the government the power to shut down autonomous AIs when they threaten national secu
arXiv:2607.19985v1 Announce Type: new Abstract: Dynamic manufacturing environments require multi-agent systems to coordinate effectively under frequent operational disturbances such as machine failure
arXiv:2507.05458v2 Announce Type: replace Abstract: For effective real-world deployment, robots should adapt to human preferences, such as balancing distance, time, and safety in delivery routing. Act
arXiv:2607.18678v1 Announce Type: new Abstract: Breast MRI is highly sensitive for detecting breast tumors, but exams contain many slices and require substantial reading time. Deep learning models oft
arXiv:2607.19394v1 Announce Type: cross Abstract: Generalizing across subjects remains challenging in invasive neural recordings because electrode configurations, anatomical structures, and neural sig
arXiv:2607.19517v1 Announce Type: new Abstract: Recovering scene-consistent 4D crowd motion from monocular video in large-scale scenes remains challenging due to severe depth ambiguity and complex sce
arXiv:2607.19528v1 Announce Type: cross Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have triggered the development of end-to-end MLLMs for autonomous driving. However, the ma
arXiv:2607.19600v1 Announce Type: cross Abstract: The shape of a planar curve is the geometric information that remains once translation, rotation, scale and reparametrisation are removed and is of in
arXiv:2607.20232v1 Announce Type: new Abstract: The training of learned inertial odometry depends on dense, high-precision position ground truth from motion capture, visual-inertial odometry or SLAM,
arXiv:2607.20352v1 Announce Type: new Abstract: Aquatic self-reconfigurable robots must assemble into desired shapes while ensuring safe interactions among multiple agents. This paper proposes a hybri
arXiv:2607.20011v1 Announce Type: cross Abstract: Traffic-utilisation measurements for network monitoring are corrupted by additive noise and statistical drift: time-dependent change in the signal's m
arXiv:2607.18958v1 Announce Type: new Abstract: While Large Vision-Language Models (LVLMs), represented by LLaVA and GPT-4V, have demonstrated remarkable capabilities, their visual inputs remain vulne
arXiv:2603.28029v2 Announce Type: replace-cross Abstract: Criticality metrics such as time-to-collision (TTC) quantify collision urgency but do not distinguish the operational consequences of false-po
arXiv:2607.19617v1 Announce Type: new Abstract: As autonomous systems and smart cities continue to evolve, the demand for efficient and robust scene understanding becomes increasingly critical. Semant
arXiv:2607.20073v1 Announce Type: new Abstract: AI-based recruitment systems that rely on machine learning models trained on historical CV data, risk perpetuating and amplifying social biases. A key c
arXiv:2607.20293v1 Announce Type: new Abstract: Diffusion policies achieve strong visuomotor control by iteratively denoising action chunks, but repeated denoising makes real-time deployment computati