Knowledge catalogue
Groups and movements that can build & get implemented clear policies will have an outsized impact on the chances that AI is used in the way that they want. This is especially true in the near term It
Here are 5 epic prompts to use with ChatGPT's new image generator. It's the most powerful image generator on the market, so let's use it to our advantage. Save this one 📌 WORK SETUP AUDIT: upload a ph
If you believe that AI is going to have a big impact on work and life, the only real tool for mitigating bad impacts and channeling usage for good will be government policy And that policy will be com
A few weeks ago, I was forwarded an email from a journalist named “Michael Chen,” asking for comment on an AI bill in Tennessee. All signs suggest Michael Chen is not a real person, and the publicatio
arXiv:2604.20990v1 Announce Type: new Abstract: Legged robots have demonstrated remarkable agility on rigid, stationary ground, but their locomotion reliability remains limited in non-inertial environ
arXiv:2603.16797v2 Announce Type: replace-cross Abstract: Guided diffusion sampling relies on approximating often intractable likelihood scores, which introduces significant noise into the sampling dy
arXiv:2604.05846v2 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly rely on agentic capabilities-iterative retrieval, tool use, and decision-making-to overcome the limits of
arXiv:2604.21103v1 Announce Type: new Abstract: Governments are increasingly interested in using AI to make administrative decisions cheaper, more scalable, and more consistent. But for probabilistic
AI is advancing faster than our ability to manage it. We still have the opportunity to build the societal and technical guardrails we need to keep people, institutions, and democracies safe — we shoul
arXiv:2604.21209v1 Announce Type: new Abstract: Online reviews have played a pivotal role in consumers' decision-making processes. Existing research has highlighted the significant impact of manageria
arXiv:2604.21827v1 Announce Type: new Abstract: Modern AI assistants are trained to follow instructions, implicitly assuming that users can clearly articulate their goals and the kind of assistance th
And eventually schools will (if they have any sense) probably withdraw or limit LLMs. 🦔Schools across the US are reversing years of technology-first classroom policies after studies show laptop and sc
Are LLMs really more important than fire or electricity? “Honestly, a ton of what we’ve developed in my lifetime amounts to scaling up the delivery of information and entertainment and the frictionles
arXiv:2601.11194v2 Announce Type: replace Abstract: We suggest a new multi-modal algorithm for joint inference of paired structurally aligned samples with Rectified Flow models. While some existing me
arXiv:2604.20844v1 Announce Type: cross Abstract: Recent GraphRAG methods integrate graph structures into text indexing and retrieval, using knowledge graph triples to connect text chunks, thereby imp
arXiv:2604.21289v1 Announce Type: new Abstract: Facial attribute editing aims to modify target attributes while preserving attribute-irrelevant content and overall image fidelity. Existing GAN-based m
arXiv:2512.06171v2 Announce Type: replace Abstract: Shearography is an interferometric technique sensitive to surface displacement gradients, providing high sensitivity for detecting subsurface defect
arXiv:2604.04395v2 Announce Type: replace Abstract: 3D conducting motion generation aims to synthesize fine-grained conductor motions from music, with broad potential in music education, virtual perfo
arXiv:2604.21854v1 Announce Type: new Abstract: Artificial intelligence now decides who receives a loan, who is flagged for criminal investigation, and whether an autonomous vehicle brakes in time. Go
arXiv:2604.21352v1 Announce Type: new Abstract: Mental health challenges are increasing worldwide, straining emotional support services and leading to counselor overload. This can result in delayed re
arXiv:2509.20712v5 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become a powerful paradigm for optimizing large language models (LLMs) to handle complex reasoning tasks. A co
arXiv:2604.21369v1 Announce Type: new Abstract: Human activity recognition (HAR) in Internet of Things (IoT) environments must cope with heterogeneous sensor settings that vary across datasets, device
arXiv:2604.21573v1 Announce Type: new Abstract: Spatial transcriptomics (ST) enables spatially resolved gene profiling but remains expensive and low-throughput, limiting large-cohort studies and routi
arXiv:2604.20869v1 Announce Type: cross Abstract: Background: More than 80% of U.S. cancer care is delivered in community settings, where survival remains worse than at academic centers. Clinicians mu
arXiv:2509.23744v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) promise enhanced reasoning by integrating diverse inputs such as text, vision, and audio. Yet cross-m
arXiv:2602.00931v2 Announce Type: replace-cross Abstract: Large language model reasoning is often treated as a monolithic capability, relying on binary preference supervision that fails to capture par
arXiv:2603.26791v2 Announce Type: replace-cross Abstract: Assessing a cited paper's impact is typically done by analyzing its citation context in isolation within the citing paper. While this focuses
arXiv:2604.20861v1 Announce Type: cross Abstract: Generative Recommendation (GR) has demonstrated remarkable performance in next-token prediction paradigms, which relies on Semantic IDs (SIDs) to comp
arXiv:2602.23408v2 Announce Type: replace-cross Abstract: The specification of the action space plays a pivotal role in imitation-based robotic manipulation policy learning, fundamentally shaping the
arXiv:2501.02576v2 Announce Type: replace Abstract: Monocular depth estimation within the diffusion-denoising paradigm demonstrates impressive generalization ability but suffers from low inference spe
arXiv:2604.21909v1 Announce Type: new Abstract: Humans and modern vision models can reach similar classification accuracy while making systematically different kinds of mistakes - differing not in how
arXiv:2604.21276v1 Announce Type: cross Abstract: As pretrained large language models replace task-specific decoders in speech recognition, a critical question arises: do their text-derived priors mak
arXiv:2604.21464v1 Announce Type: cross Abstract: Standard reinforcement learning (RL) optimizes policies for reward but imposes few constraints on how decisions evolve over time. As a result, policie
arXiv:2604.21733v1 Announce Type: new Abstract: The increasing integration of artificial intelligence (AI) in higher education has raised important questions regarding students' transparency in report
arXiv:2604.21668v1 Announce Type: new Abstract: The world knowledge and reasoning capabilities of text-based large language models (LLMs) are advancing rapidly, yet current approaches to human motion
arXiv:2604.21554v1 Announce Type: new Abstract: Under the EU AI Act, translating AI governance requirements into software development practice remains challenging. While AI governance frameworks exist
arXiv:2512.05591v2 Announce Type: replace-cross Abstract: Large language model post-training relies on reinforcement learning to improve model capability and alignment quality. However, the off-policy
arXiv:2604.21907v1 Announce Type: cross Abstract: Equity Bias is a philosophical and practical framework for building smarter, more equitable AI systems. Grounded in hermeneutic philosophy and epistem
arXiv:2604.20854v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds language models in factual evidence but introduces critical challenges regarding knowledge conflicts betw
arXiv:2604.20972v1 Announce Type: new Abstract: Content moderation systems are typically evaluated by measuring agreement with human labels. In rule-governed environments this assumption fails: multip
arXiv:2510.18914v4 Announce Type: replace-cross Abstract: Large language models often display undesirable behaviors embedded in their internal representations, undermining fairness, inconsistency drif
arXiv:2604.21711v1 Announce Type: cross Abstract: Fair machine learning (ML) methods help identify and mitigate the risk that algorithms encode or automate social injustices. Algorithmic approaches al
arXiv:2604.21420v1 Announce Type: new Abstract: Quality Estimation (QE) aims to assess machine translation quality without reference translations, but recent studies have shown that existing QE models
arXiv:2604.21667v1 Announce Type: cross Abstract: Beyond exploring disaggregated labels for modeling perspectives, annotator rationales provide fine-grained signals of individual perspectives. In this
arXiv:2604.21331v1 Announce Type: new Abstract: The current practice of dexterous manipulation generally relies on a single wrist-mounted view, which is often occluded and limits performance on tasks
arXiv:2506.09998v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can often accurately describe probability distributions using natural language, yet they still struggle to genera
arXiv:2604.21716v1 Announce Type: new Abstract: Prior work evaluates code generation bias primarily through simple conditional statements, which represent only a narrow slice of real-world programming
arXiv:2509.23649v2 Announce Type: replace-cross Abstract: Generative recommendation, which directly generates item identifiers, has emerged as a promising paradigm for recommendation systems. However,
arXiv:2604.21321v1 Announce Type: new Abstract: Monitoring frying oil degradation is critical for food safety, yet current practice relies on destructive wet-chemistry assays that provide no spatial i
arXiv:2604.21189v1 Announce Type: new Abstract: Collision avoidance for robotic manipulators requires enforcing full-body safety constraints in high-dimensional configuration spaces. Control Barrier F
arXiv:2604.21830v1 Announce Type: new Abstract: We present GFlowState, a visual analytics system designed to illuminate the training process of Generative Flow Networks (GFlowNets or GFNs). GFlowNets
arXiv:2601.05019v2 Announce Type: replace-cross Abstract: Recent Large Reasoning Models trained via reinforcement learning exhibit a 'natural' alignment with human cognitive costs. However, we show th
arXiv:2604.20938v1 Announce Type: cross Abstract: Long-horizon language-model agents are dominated, in lines of code and in operational complexity, not by their underlying model but by the harness tha
arXiv:2604.21741v1 Announce Type: new Abstract: Post-training is essential for turning pretrained generalist robot policies into reliable task-specific controllers, but existing human-in-the-loop pipe
arXiv:2604.21045v1 Announce Type: new Abstract: Simultaneous speech translation (SST) generates translations while receiving partial speech input. Recent advances show that large language models (LLMs
arXiv:2604.21496v1 Announce Type: new Abstract: Human-elephant conflict (HEC) is rising across India as habitat loss and expanding human settlements force elephants into closer contact with people. Wh
arXiv:2602.19208v2 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective for Large Language Model (LLM) reasoning, yet current methods face
arXiv:2604.21192v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) have been extensively used in robotics applications, achieving great success in various manipulation problems. Mo
arXiv:2512.09292v2 Announce Type: replace-cross Abstract: The meteoric rise in text generation capability has been accompanied by parallel growth in interest in machine-generated text detection: the c
In 1982, Blade Runner was speculation. In 2026, it's the conversation. Memory, personhood, alignment, what we owe the minds we build. Watching it Thursday 28 May, Kensington Central Library. Come thin