Knowledge catalogue
arXiv:2602.11198v2 Announce Type: replace-cross Abstract: Multi-agent frameworks (MAFs) promise to simplify LLM-driven software development, yet no principled metric captures how well AI coding assist
arXiv:2607.11919v1 Announce Type: cross Abstract: Human memory is reconstructive, not a faithful recording. Current multimodal LLMs (MLLMs) lack this capability: they process images through a frozen v
arXiv:2607.11981v1 Announce Type: cross Abstract: Aggregate reliability estimates can obscure heterogeneity in measurement-design burden across response conditions, so a single G- or D-study may misch
arXiv:2607.11963v1 Announce Type: cross Abstract: The early detection of Chronic Kidney Disease using machine learning has attracted significant interest in healthcare-related computer science. Despit
arXiv:2607.12527v1 Announce Type: new Abstract: Musculoskeletal diseases are among the leading causes of disability worldwide and create the greatest global need for rehabilitation. Because recovery,
Extracting information from millions of documents at scale used to take an insane number of human hours. Even with recent OCR + document AI tech, humans would still have to spend a lot of time careful
arXiv:2607.12687v1 Announce Type: cross Abstract: LLMs can perform language-based quantitative prediction from unstructured inputs, but remain susceptible to hallucinations and overconfident errors, m
arXiv:2607.12474v1 Announce Type: new Abstract: Recent advances in foundation models have transformed AI for Science, enabling remarkably accurate predictive performance across domains ranging from pr
arXiv:2607.11978v1 Announce Type: cross Abstract: Precision molecular design aims to discover personalized drug candidates through joint control of multiple conditions, such as biological relevance an
arXiv:2607.09224v2 Announce Type: replace-cross Abstract: Version control systems are essential for collaborative software development, yet tools like git remain challenging for many practitioners. Re
Grok 4.5 is worth trying Grok 4.5 just ranked #2 on the FrontierSWE leaderboard, outperforming Claude Opus 4.8 and GPT-5.5 It delivers top-tier coding performance with exceptional speed, strong token
arXiv:2510.18315v2 Announce Type: replace-cross Abstract: We investigate how embedding dimension affects the emergence of an internal 'world model' in a transformer trained with reinforcement learning
arXiv:2603.28583v2 Announce Type: replace-cross Abstract: Despite the success of Vision-Language Models (VLMs), misleading charts remain a significant challenge due to their deceptive visual structure
Note the current expectations are still around test time compute/more tokens for a given task This is not the case Tokens per task will now drop even as quality improves Cost per intelligence equivale
arXiv:2607.12911v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly used for dietary assessment from meal images, where retrieval-augmented grounding was shown to
arXiv:2607.12085v1 Announce Type: new Abstract: Evaluating retail conversational agents requires methods beyond lexical-overlap metrics to assess intent alignment, factuality, helpfulness, clarity, to
arXiv:2607.11977v1 Announce Type: new Abstract: In 2019, OpenAI released two million GPT-2 outputs-ungrammatical, half broken-to aid the detection of machine-generated text. The alignment that produce
What it is: ATH-MaaS/OvisOCR2 - a 0.8B document-parsing VLM post-trained from Qwen3.5-0.8B (SFT + RL + OPD), Apache 2.0, runs on vLLM 0.22.1. One prompt per page image -> complete markdown (HTML table
arXiv:2607.12335v1 Announce Type: new Abstract: Prototype-based networks provide inherently interpretable classification by linking predictions to learned exemplars, but their use in 3D point clouds a
arXiv:2607.10541v2 Announce Type: replace-cross Abstract: Sequential recommender systems typically infer user preferences through single-pass encoding of interaction histories without iterative refine
arXiv:2607.12985v1 Announce Type: new Abstract: Aligned language models routinely misreport under non-evidential incentive pressure: they agree with a confident user or overstate certainty even when t
arXiv:2607.11920v1 Announce Type: cross Abstract: Evaluating decisions made under uncertainty is hard when labeled outcomes are scarce, costly, or confounded with luck. We treat subjective expected ut
arXiv:2607.12963v1 Announce Type: new Abstract: As large language models (LLMs) grow more capable, they are increasingly deployed in context-rich settings where task inputs are often accompanied by lo
arXiv:2607.12863v1 Announce Type: cross Abstract: Transformer language models are increasingly used as software components, yet biased outputs remain difficult to localize and repair inside the model.
arXiv:2607.11939v1 Announce Type: new Abstract: Accurate pedestrian trajectory prediction in crowded environments remains challenging due to the multimodal uncertainty of human motion and the variable
arXiv:2607.12356v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a powerful end-to-end paradigm for robotic manipulation by mapping language instructions and 2D visu
arXiv:2607.12304v1 Announce Type: new Abstract: A score on a temporal video question answering benchmark is meant to measure that a model has temporal understanding, but it conflates two questions. 1.
arXiv:2602.16918v2 Announce Type: replace-cross Abstract: We present Xray-Visual, a unified vision model architecture for large-scale image and video understanding trained on industry-scale social med
Retail Finance teams are increasingly deploying agentic AI to safeguard omni‑channel margins. These systems automatically monitor sales performance, forecast demand, and adjust pricing or inventory co
I want to have this in writing so I can refer back to this tweet before it inevitably becomes a consensus view on twitter and say 'I told you so!' - The mass majority of researchers and academics in d
The automotive industry is moving from building hardware-centric platforms toward building their own sophisticated Software-Defined Vehicle (SDV) architectures. For OEMs, a vehicle is no longer just a
The Anglo-Scottish Enlightenment – the real antidote to Rousseau and Voltaire The French Enlightenment and the Anglo-Scottish Enlightenment happened simultaneously, in the same century, reading the sa
arXiv:2510.22052v2 Announce Type: replace Abstract: The field of artificial intelligence (AI) has taken a tight hold on broad aspects of society, industry, business, and governance in ways that dictat
arXiv:2607.08299v1 Announce Type: new Abstract: Accurate and timely diagnoses are essential for quality patient care. However, delayed recommendation of diagnostic tests and physicians' subjective int
arXiv:2607.08359v1 Announce Type: cross Abstract: Vision-Language Navigation (VLN) enables UAV autonomous navigation in unknown environments by mapping language instructions to real-time visual inputs
arXiv:2607.08579v1 Announce Type: cross Abstract: Missing data is a persistent obstacle in scientific, social science, and public health research, often biasing analyses and placing accountability on
arXiv:2607.08182v1 Announce Type: cross Abstract: Vision-language-action (VLA) models aim to map multimodal inputs to robot actions. However, most existing approaches struggle to cover complex dynamic
arXiv:2607.07903v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit remarkable capabilities but remain highly vulnerable to adversarial prompts and jailbreak attacks. Existing appro
arXiv:2607.08233v1 Announce Type: new Abstract: A central challenge in building intelligent systems is enabling agents to jointly perceive complex inputs, form hypotheses about hidden patterns, and de
arXiv:2607.08056v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) have recently achieved substantial progress in natural language generation tasks. Recent research demonstrates that a
arXiv:2607.07762v1 Announce Type: new Abstract: Modern machine learning (ML) increasingly relies on complex models whose behavior is difficult to characterize beyond empirical performance metrics. Acr
arXiv:2607.08284v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated rapidly improving long-context capabilities, prompting a wave of benchmarks designed to evaluate them. Ho
arXiv:2607.08537v1 Announce Type: new Abstract: The recently established 'Out of Sight, Not out of Mind' (OSNOM) task for egocentric videos focuses on tracking objects that are moved by the camera wea
GPT-5.6 Sol achieved a breakthrough by becoming the first verified frontier AI model to surpass performance on ARC-AGI-3, scoring 7.8% and setting a new state-of-the-art benchmark. ARC-AGI (Abstractio
arXiv:2607.07422v1 Announce Type: new Abstract: Logical Multi-Hop Query Answering over Knowledge Graphs (KGs) can be formulated as querying, with an implicit completeness assumption. Current works mai
arXiv:2511.18735v3 Announce Type: replace-cross Abstract: In this work, we define Foresight Intelligence as the capability to anticipate and interpret future events-an ability essential for applicatio
arXiv:2601.21476v2 Announce Type: replace Abstract: On-policy reinforcement learning (RL) for language model post-training suffers from a fundamental tension: as training progresses, policy entropy co
arXiv:2606.13566v2 Announce Type: replace Abstract: Current discussions of AI in scientific discovery are often dominated by two visible capabilities: search over existing knowledge and execution thro
arXiv:2607.05859v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are promising for construction-site monitoring, and recent construction-tailored VLMs have primarily adapted pretrained VL
arXiv:2606.22511v2 Announce Type: replace Abstract: In open-ended generation, LLMs frequently fall into the 'likelihood trap', marked by repetitive degeneration and vocabulary dullness, creating a dis
arXiv:2607.06534v1 Announce Type: new Abstract: Existing 3D scene-grounded Large Language Models (3D-LLMs) focus on answering questions grounded in simplified single-room 3D scenes, lacking the abilit
arXiv:2607.05465v1 Announce Type: cross Abstract: Complex image creation and editing often require more than a single generation or editing model. A user request may involve synthesizing images, local
arXiv:2607.05462v1 Announce Type: cross Abstract: As AI agents are incorporated into life science workflows, the capabilities that speed discovery might also enable misuse. We present BioSecBench-Refu
arXiv:2607.06564v1 Announce Type: cross Abstract: Recently, Vision-Language-Action (VLA) models have demonstrated strong generalization across diverse tasks. However, effective robotic manipulation in
arXiv:2607.05545v1 Announce Type: cross Abstract: LLM conformity is often used to describe cases where a model changes a correct answer toward a peer or group response. We show that most of this appar
arXiv:2602.00846v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) struggle with alignment due to the limitations of existing reward models (RMs), which are predominantly vis
arXiv:2406.07089v4 Announce Type: replace Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have shown promise for remote sensing tasks such as visual question answering and scene
arXiv:2607.06527v1 Announce Type: cross Abstract: Multi-hop Question Answering over Knowledge Graphs faces a critical challenge: traditional retrieve-then-read pipelines break differentiability, preve
arXiv:2507.04136v2 Announce Type: replace Abstract: This survey offers a comprehensive foundation on the integration of RL with language models, highlighting prominent algorithms such as Proximal Poli
arXiv:2607.04426v1 Announce Type: new Abstract: Embodied AI is moving from isolated perception or action modules toward physical agents that understand, plan under goals, act through robot bodies, mon