Knowledge catalogue
arXiv:2604.16243v1 Announce Type: new Abstract: Reinforcement learning has advanced video reasoning in large multi-modal models, yet dominant pipelines either rely on on-policy self-exploration, which
arXiv:2604.15488v1 Announce Type: cross Abstract: Large language models (LLMs) often exhibit undesirable behaviors, such as safety violations and hallucinations. Although inference-time steering offer
arXiv:2604.15614v1 Announce Type: new Abstract: This paper proposes a novel method that incorporates empowerment when reasoning actions in reinforcement learning (RL), thereby achieving the flexibilit
arXiv:2504.01137v3 Announce Type: replace Abstract: Text-to-image generation models suffer from alignment problems, where generated images fail to accurately capture the objects and relations in the t
arXiv:2604.15948v1 Announce Type: new Abstract: Text-guided image editing, a pivotal task in modern multimedia content creation, has seen remarkable progress with training-free methods that eliminate
arXiv:2604.15800v1 Announce Type: cross Abstract: This study presents WriteFlow, an AI voice-based writing assistant designed to support reflective academic writing through goal-oriented interaction.
arXiv:2604.16282v1 Announce Type: new Abstract: Stochastic dynamical systems with slow or metastable behavior evolve, on long time scales, on an unknown low-dimensional manifold in high-dimensional am
arXiv:2604.15602v1 Announce Type: new Abstract: Preference optimization is widely used to align Large Language Models (LLMs) with preference feedback. However, most existing methods train on a single
arXiv:2604.15923v1 Announce Type: cross Abstract: Video-to-Speech (VTS) generation aims to synthesize speech from a silent video without auditory signals. However, existing VTS methods disregard the h
arXiv:2604.15331v1 Announce Type: cross Abstract: We analyze over 500,000 de-identified health-related conversations with Microsoft Copilot from January 2026 to characterize what people ask conversati
This newsletter covers three main topics: advances in automating alignment research to improve AI safety processes, a safety evaluation study of a Chinese AI model, and technical details about HiFloat
Importantly, the tweet by @itsolelehmann may be misleading. I stand by what I said but have some reason to think that @AmandaAskell’s views may have been misrepresented. Seeking clarification and will
arXiv:2604.15701v1 Announce Type: new Abstract: The significant computational demands of large language models have increased interest in distilling reasoning abilities into smaller models via Chain-o
arXiv:2512.12858v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in business-critical domains such as finance, education, healthcare, and customer suppo
arXiv:2603.11331v2 Announce Type: replace-cross Abstract: Adversarial attacks can reliably steer safety-aligned large language models toward unsafe behavior. Empirically, we find that strong adversari
Je suis passé à Découverte de @CBCRadioCanada pour discuter des risques de l’IA, des raisons scientifiques qui expliquent certains des comportements inquiétants des modèles de pointe, et des solutions
arXiv:2604.16247v1 Announce Type: cross Abstract: We propose HILBERT (HIerarchical Long-sequence Balanced Embedding with Reciprocal contrastive Training), a cross-attentive multimodal framework for le
arXiv:2512.04847v2 Announce Type: replace-cross Abstract: Pre-trained audio models excel at detecting acoustic patterns in auscultation sounds but often fail to grasp their clinical significance, limi
arXiv:2604.15744v1 Announce Type: new Abstract: This thesis investigates geographic dialect alignment in place-informed social media communities, focussing on New Zealand-related Reddit communities. B
arXiv:2412.19363v3 Announce Type: replace Abstract: Large Language Models (LLMs) have transformed artificial intelligence by excelling in complex natural language processing tasks. Their ability to ge
arXiv:2604.15853v1 Announce Type: new Abstract: Automated Aesthetic Quality Assessment (AQA) treats images primarily as static pixel vectors, aligning predictions with human-rating scores largely thro
literally my basic model since 1998. crazy that some people still haven’t figured this out. My basic model of capabilities: LLMs are good at problems similar to those that appear in their training dat
LLMs are “ good at math style problems, where you tell them A, B and C are true, and then ask them to figure out D [but] extremely bad at anything involving what I would call mature scholarship .. [so
arXiv:2604.15671v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated significant potential for embodied decision-making; however, their application in complex chemical
arXiv:2604.15377v1 Announce Type: cross Abstract: Accurate and timely rainfall nowcasting is crucial for disaster mitigation and water resource management. Despite recent advances in deep learning, pr
arXiv:2601.03633v2 Announce Type: replace-cross Abstract: Accurate and high-resolution precipitation nowcasting from radar echo sequences is crucial for disaster mitigation and economic planning, yet
arXiv:2604.15757v1 Announce Type: new Abstract: This research note identifies a previously overlooked distinction between multi-objective reinforcement learning (MORL), and more conventional single-ob
arXiv:2604.16146v1 Announce Type: new Abstract: Recent works proposed test-time alignment methods that rely on a small aligned model as a proxy that guides the generation of a larger base (unaligned)
Artificial intelligence infrastructure is now the deciding force behind enterprise competitiveness. What was once a backend concern has moved directly into the center of business strategy, shaping how
arXiv:2604.15455v1 Announce Type: new Abstract: Given a demonstration, a robot should be able to generalize a skill to any object it encounters-but existing approaches to skill transfer often fail to
OpenAI’s market share is slipping. ChatGPT is dying. OpenAI lost the crown as their market share fell below 40 percent for the first time ever. It stands at just 38.7 percent now after four straight m
Aditya Kalra / Reuters: Order: India's CCI sets May hearing on penalties after Apple failed to submit info on alleged app market abuse; Apple said it fears it could be fined up to $38B — Apple has not
arXiv:2604.15585v1 Announce Type: cross Abstract: Predicting the relative value of any given chess piece in a position remains an open challenge, as a piece's contribution depends on its spatial relat
arXiv:2506.20020v2 Announce Type: replace Abstract: Reasoning in humans is prone to biases due to underlying motivations like identity protection, that undermine rational decision-making and judgment.
arXiv:2604.15770v1 Announce Type: new Abstract: Accurate open-vocabulary 3D scene understanding requires semantic representations that are both language-aligned and spatially precise at the pixel leve
arXiv:2604.15558v1 Announce Type: new Abstract: Deliberative multi-agent systems allow agents to exchange messages and revise beliefs over time. While this interaction is meant to improve performance,
arXiv:2604.16076v1 Announce Type: cross Abstract: Concept Bottleneck Models (CBMs) aim to improve interpretability in Deep Learning by structuring predictions through human-understandable concepts, bu
arXiv:2602.13088v2 Announce Type: replace-cross Abstract: The distinction between genuine grassroots activism and automated influence operations is collapsing. While contemporary policy debates priori
arXiv:2604.16106v1 Announce Type: cross Abstract: The Project of AI is a world-building endeavor, wherein those who fund and develop AI systems both operate through and seek to sustain networks of pow
arXiv:2510.10959v3 Announce Type: replace-cross Abstract: Reasoning ability has become a defining capability of Large Language Models (LLMs), with Reinforcement Learning with Verifiable Rewards (RLVR)
arXiv:2604.15577v1 Announce Type: cross Abstract: Consider an auto-regressive model that produces outputs x (e.g., answers to questions, molecules) each of which can be summarized by an attribute vect
arXiv:2604.15856v1 Announce Type: cross Abstract: Multimodal remote sensing data provide complementary information for semantic segmentation, but in real-world deployments, some modalities may be unav
arXiv:2604.16090v1 Announce Type: cross Abstract: Probabilistic Synchronous Parallel (PSP) is a technique in distributed learning systems to reduce synchronization bottlenecks by sampling a subset of
arXiv:2604.15524v1 Announce Type: cross Abstract: This paper presents a novel density control framework for multi-robot systems with spatial safety and energy sustainability guarantees. Stochastic rob
arXiv:2604.16033v1 Announce Type: cross Abstract: Buildings account for approximately 40% of global energy consumption, and with the growing share of intermittent renewable energy sources, enabling de
arXiv:2604.16111v1 Announce Type: new Abstract: We study the sample complexity of learning an epsilon-optimal policy in the Stochastic Shortest Path (SSP) problem. We first derive sample complexity bo
arXiv:2504.13541v5 Announce Type: replace-cross Abstract: Training resource-constrained autonomous agents on multiple tasks simultaneously is crucial for adapting to diverse real-world environments. R
arXiv:2503.05578v4 Announce Type: replace Abstract: Pose estimation-guided unseen object 6-DoF robotic manipulation is a key task in robotics. However, the scalability of current pose estimation metho
arXiv:2604.15794v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable success, underpinning diverse AI applications. However, they often suffer from performance degra
Seriously. If you don’t understand the below, you really shouldn’t speculate about AI. It’s absolutely fundamental. literally my basic model since 1998. crazy that some people still haven’t figured th
arXiv:2604.15628v1 Announce Type: cross Abstract: Cross-modal retrieval between food images and recipe texts is an important task with applications in nutritional management, dietary logging, and cook
arXiv:2604.15771v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has emerged as a foundational paradigm for grounding large language models in external knowledge. While adaptive re
arXiv:2604.15559v1 Announce Type: new Abstract: Recent work on subliminal learning demonstrates that language models can transmit semantic traits through data that is semantically unrelated to those t
arXiv:2604.15579v1 Announce Type: cross Abstract: AI agents that interact with their environments through tools enable powerful applications, but in high-stakes business settings, unintended actions c
arXiv:2604.16224v1 Announce Type: cross Abstract: As a relatively new forum, ACM FAccT has become a key space for activists and scholars to critically examine emerging AI and ML technologies. It bring
arXiv:2604.14646v2 Announce Type: replace Abstract: Recent advances in reinforcement learning (RL) have improved the reasoning capabilities of large language models (LLMs) and vision-language models (
arXiv:2604.15383v1 Announce Type: cross Abstract: Large audio-language models (LALMs) generalize across speech, sound, and music, but unified decoders can exhibit a temporal smoothing bias: transient
The AI industry insists they can manage the risks of superintelligence, but there are in fact zero widely agreed on or accepted solutions to the problem of how one could even control something vastly
arXiv:2604.16087v1 Announce Type: new Abstract: We study the problem of learning in zero-sum matrix games with repeated play and bandit feedback. Specifically, we focus on developing uncoupled algorit
arXiv:2603.01283v2 Announce Type: replace Abstract: Deployed RL agents operate in closed-loop systems where reliable performance depends on maintaining coherent coupling between observations, actions,