Knowledge catalogue
arXiv:2606.03467v1 Announce Type: new Abstract: LLM-based multi-agent systems exhibit remarkable collaborative capabilities in complex multi-step tasks. However, these systems are highly sensitive to
Computex 2024 is expected to feature significant announcements around local AI deployment, with major industry players including NVIDIA and Microsoft actively promoting and discussing on-device AI wor
arXiv:2601.23229v2 Announce Type: replace Abstract: Markov decision processes (MDPs) are a fundamental model in sequential decision making. Robust MDPs (RMDPs) extend this framework by allowing uncert
arXiv:2606.03508v1 Announce Type: new Abstract: Printed circuit board (PCB) defect detection is an essential part of automated optical inspection (AOI); yet it remains challenging in practice because
arXiv:2606.03247v1 Announce Type: new Abstract: Document-grounded dialogue systems (DGDS) utilize knowledge from external documents to answer domain-specific user questions. Existing solutions typical
arXiv:2406.10407v3 Announce Type: replace-cross Abstract: Semidefinite programs (SDPs) and their solvers are powerful tools with many applications in machine learning and data science. Designing scala
Suno - a company that trained on 'essentially all music files of reasonable quality that are accessible on the open Internet', and argues it does not need to pay to do so - is now valued at $5.4 billi
Richard Milne / Financial Times: Supercell, King, and Sybo warn that EU's Digital Fairness Act, requiring pop-ups showing real-world values of virtual currencies, could make games “unplayable” — Maker
arXiv:2606.02642v1 Announce Type: cross Abstract: Despite the success of audio-visual large-language models (LLMs), they can produce plausible but ungrounded outputs, termed hallucination. Existing be
@swyx and I are curating the AI in GTM track at @aiDotEngineer on June 30. The thing every AI engineer must realize: GTM just became an engineering problem. Outbound = agent design. Enrichment = retri
arXiv:2606.03348v1 Announce Type: cross Abstract: Recent generative models can now produce visual artifacts with realistic embedded text and layouts, creating a new misinformation threat: synthetic cr
arXiv:2606.03892v1 Announce Type: cross Abstract: Training LLMs to orchestrate multi-step tool calls is held back by three coupled obstacles: realistic stateful execution environments are costly to bu
arXiv:2606.03130v1 Announce Type: new Abstract: Small open-source code models that power IDE autocomplete still emit hallucinated Fill-in-the-Middle (FIM) completions: syntactically natural calls to m
arXiv:2512.21094v2 Announce Type: replace Abstract: Text-to-Audio-Video (T2AV) generation aims to synthesize temporally coherent video and semantically synchronized audio from natural language, yet it
arXiv:2606.02624v1 Announce Type: cross Abstract: AI for scientific discovery is entering an agentic era, where protein-engineering systems are expected to prioritize future wet-lab experiments rather
arXiv:2606.03866v1 Announce Type: cross Abstract: Scaling recommender systems via large language models (LLMs) has become a prominent trend in the industry. However, aligning the LLM's semantic space
arXiv:2606.03332v1 Announce Type: new Abstract: Probabilistic models are typically trained using task-agnostic objectives like log-loss, which can lead to significant errors in downstream estimation.
arXiv:2509.09685v5 Announce Type: replace-cross Abstract: We present TalkPlayData 2, a synthetic dataset for multimodal conversational music recommendation generated by an agentic data pipeline. In th
arXiv:2606.02645v1 Announce Type: cross Abstract: Periodic target updates in Q-learning and soft target updates in actor-critic methods are empirically well established stabilization mechanisms, but t
arXiv:2606.03314v1 Announce Type: new Abstract: High-fidelity semantic 3D scene representations are crucial for numerous applications, including robotics, autonomous driving, and simulation. Beyond th
arXiv:2606.03802v1 Announce Type: new Abstract: Objective: Consumer face camera remote photoplethysmography (rPPG) enables passive cardiovascular monitoring, but whether single-cycle waveform morpholo
arXiv:2511.04421v2 Announce Type: replace Abstract: Action chunking is a widely adopted approach in Learning from Demonstration (LfD). By modeling multi-step action chunks rather than single-step acti
arXiv:2606.02872v1 Announce Type: cross Abstract: This paper considers the problem of simultaneously controlling an interceptor's impact time and impact angle using its lateral acceleration as the sol
arXiv:2602.10387v2 Announce Type: replace-cross Abstract: Traditional query optimization relies on cost-based optimizers that estimate execution cost (e.g., runtime, memory, and I/O) using predefined
arXiv:2606.03606v1 Announce Type: cross Abstract: Large language models achieve strong performance on arithmetic reasoning benchmarks, and one common response to arithmetic brittleness is to delegate
arXiv:2510.20372v4 Announce Type: replace-cross Abstract: Small influential data subsets can dramatically impact model conclusions, with a few data points overturning key findings. While recent work i
arXiv:2606.02601v1 Announce Type: new Abstract: Within-dataset class-split evaluation is widely used as a proxy for fully unconditional out-of-distribution anomaly detection. We show that this protoco
arXiv:2606.03806v1 Announce Type: new Abstract: Temperature-emissivity-texture (TeX) decomposition seeks to recover object heat state, material spectral response, and visible-like geometric texture fr
arXiv:2606.03839v1 Announce Type: new Abstract: Text-Attributed Graph (TAG) is an important type of graph structured data, where each node has a text description. TAG models usually train a Graph Neur
arXiv:2606.03715v1 Announce Type: new Abstract: Text-to-image models rely on text prompts as their primary interface to human intent. Prompts are encoded by a text encoder into embeddings that conditi
arXiv:2606.03075v1 Announce Type: new Abstract: Vision-Language Models (VLMs) inherit the auto-regressive generation paradigm and cache the keys and values (KV) of all previous tokens to accelerate in
Thanks @hwchase17 @bryonkuchML for the inspiration and the nudge from @MEGAcodePaul - took your feedback seriously. I have developed a boilerplate that covers the full optimization loop that productio
arXiv:2601.08173v2 Announce Type: replace Abstract: The rapid evolution of Multi-modal Large Language Models (MLLMs) has advanced workflow automation; however, existing research mainly targets perform
the best agents aren't just built with the best models: they're built with harnesses purpose-built for the task at hand here's a guide on how to build a harness that's really good at feeding the model
arXiv:2606.03686v1 Announce Type: new Abstract: We present DeepSpeak-Agentic, a dataset of videos comprising over 37 hours of semi-structured conversations between a human and an embodied AI agent. We
arXiv:2606.03032v1 Announce Type: new Abstract: Multi-agent LLM systems often treat consensus as evidence of successful interaction. For deliberative problems, however, reliability depends on whether
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. 5 key points in Trump’s new AI order Less than two weeks after
arXiv:2501.02173v2 Announce Type: replace-cross Abstract: The deployment of Large Language Models (LLMs) in recommender systems for predicting Click-Through Rates (CTR) necessitates a delicate balance
arXiv:2606.02867v1 Announce Type: cross Abstract: Human behaviour during epidemics affects infectious disease dynamics, but quantifying this remains deeply challenging. Here we introduce the Epi-LLM f
arXiv:2606.03043v1 Announce Type: new Abstract: LMs-as-judges are now standard, yet judges agree strongly with one another while agreeing only weakly with humans. We test whether this reflects shared
arXiv:2606.02911v1 Announce Type: new Abstract: Current research primarily focuses on model performance, while comparatively less attention has been devoted to uncertainty estimation, particularly in
The Hermes Web Dashboard has been significantly redesigned to function as a comprehensive admin panel with full feature parity, allowing users to manage all operations directly through a web browser i
arXiv:2606.03907v1 Announce Type: cross Abstract: Agentic AI coding tools write code with increasing autonomy and in doing so decide when to import a library and when to implement functionality from s
arXiv:2606.03358v1 Announce Type: new Abstract: Smart meter data can reveal sensitive socio-demographic characteristics of households, raising privacy concerns. While this risk has been demonstrated a
Google has open-sourced its flood forecasting framework, which replicates operational FloodHub model training settings and reflects methodology described in a 2024 Nature paper for global ungauged flo
The Prime Minister says “lessons must be learned” over the death of Henry Nowak. He then goes on to say “there is no two-tier policing” despite being read a line by Nigel Farage, from the Police racis
THE PROMPT THAT REPLACES YOUR WORKFLOW AUDIT: You are my business transformation strategist. I want you to find the real AI-era business transformation hiding inside my work by starting from goals, bu
arXiv:2606.03305v1 Announce Type: new Abstract: Benchmark contamination, where evaluation examples appear in a model's training data, threatens the validity of LLM assessment. Statistical tools for de
arXiv:2606.02646v1 Announce Type: cross Abstract: Inference-time multi-agent LLM scaling lacks a shared unit: counting nominal agents conflates cost with independent evidence. We derive a two-paramete
arXiv:2606.02956v1 Announce Type: new Abstract: Existing autonomous driving datasets have enabled major progress, but fall short in sensor fidelity, map completeness, or geographic diversity. We prese
arXiv:2606.03092v1 Announce Type: new Abstract: Inference-time scaling has emerged as a critical avenue for enhancing Large Language Models' performance, yet real-world deployment is constrained by st
arXiv:2606.03645v1 Announce Type: cross Abstract: Large Language Models exhibit paradoxical fragility in fundamental arithmetic, implying a disconnect between internal computation and discrete output.
This article profiles the team and processes behind DigitalOcean's Deploy product, which enables users to ship AI applications to production. It likely covers the engineering approach, team structure,
arXiv:2606.03357v1 Announce Type: cross Abstract: When prompting SLMs for psychometric assessments, researchers assume the outputs reflect semantic reasoning. We evaluate this premise across 13 open-w
Greg Miller / Washington Post: The US and other Five Eyes nations warn that China is flooding online job platforms with fake profiles and offers targeting government and military personnel — Nations i
Katherine Blunt / Wall Street Journal: The US data center build-out is falling behind schedule; JP Morgan says 60%+ of data center capacity planned for completion in 2027 isn't yet under construction
arXiv:2606.03326v1 Announce Type: new Abstract: Compliance pipelines detect violations as transient query results and do not keep the violation itself as a persistent graph object with review state, a
The West has created an utterly evil state religion where an accusation of “racism” is the gravest offense that can be committed, even worse than rape or murder! So if police show up at a crime scene
arXiv:2606.03250v1 Announce Type: new Abstract: Digital healthcare generates vast amounts of clinical text that can support AI-assisted applications, yet German biomedical language models remain limit
arXiv:2606.02758v1 Announce Type: cross Abstract: We introduce Lie groupoid equivariant neural networks as a specialization of recently proposed topological category-equivariant neural networks to the