Knowledge catalogue
arXiv:2608.10513v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) remain vulnerable to jailbreak attacks that exploit visual inputs to bypass safety alignment inherited from their
arXiv:2602.13319v2 Announce Type: replace Abstract: Perspective-aware AI requires modeling evolving internal states---goals, emotions, contexts---not merely preferences. Progress is limited by a data
arXiv:2608.10692v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as mobile assistants, where a key challenge is leveraging personal information scattered across
arXiv:2608.10474v1 Announce Type: cross Abstract: Popularity bias in recommendation systems arises when a majority user class generates disproportionate interaction data, causing the system to increas
arXiv:2608.11191v1 Announce Type: cross Abstract: GUI Visual Grounding is a fundamental capability for GUI agents. Existing models typically freeze their parameters after deployment, limiting their ab
arXiv:2608.00961v2 Announce Type: replace-cross Abstract: AI anthropomorphism is typically treated as a problem of user misperception requiring institutional correction. Users who engage in sustained
arXiv:2608.10176v1 Announce Type: new Abstract: Public service chatbots are expected to deliver recommendations from an underlying public service directory, while also making sure that the recommendat
arXiv:2608.10522v1 Announce Type: cross Abstract: While vision-language models dominate medical representation learning, unstructured text lacks the dense, quantitative diagnostic phenotypes inherent
arXiv:2608.10489v1 Announce Type: new Abstract: Abundant visual information strengthens vision-language model (VLM) perception, yet massive visual tokens raise inference costs. Existing visual token p
arXiv:2608.11095v1 Announce Type: new Abstract: Agentic coding READMEs like CLAUDE.md grow without bound in real repositories, stopping only when the repository retires or someone rewrites the file wh
arXiv:2608.11022v1 Announce Type: cross Abstract: Model Cards and Data Cards have demonstrated the value of structured, human-readable documentation for machine learning artifacts, capturing their con
arXiv:2501.17629v2 Announce Type: replace-cross Abstract: Several studies claim that large language models have passed the Turing Test and hence can 'think', yet none follow Turing's original instruct
arXiv:2608.09289v1 Announce Type: new Abstract: Second language writing research distinguishes grammatical accuracy from native-like idiomaticity, yet automated writing evaluation often conflates thes
arXiv:2608.09476v1 Announce Type: cross Abstract: Cowork agents may complete benign tasks while disclosing protected data, manipulating unauthorized state, invocate unauthorized API. We define behavio
arXiv:2608.09142v1 Announce Type: new Abstract: Treatment planning in precision oncology requires synthesizing heterogeneous patient information with rapidly evolving clinical guidelines to ensure gui
arXiv:2606.21597v2 Announce Type: replace-cross Abstract: The open-source ecosystem on GitHub lacks a systematic hierarchical taxonomy of software repositories. GitHub Topics, the dominant organizatio
arXiv:2608.07873v1 Announce Type: new Abstract: We introduce the workbook time machine, a pipeline that automatically creates benchmarks evaluating the ability of language models to create derived obj
arXiv:2508.16481v3 Announce Type: replace Abstract: Ensuring the safe use of agentic systems requires a thorough understanding of the range of malicious behaviors these systems may exhibit. In this pa
arXiv:2603.12658v2 Announce Type: replace-cross Abstract: Continual learning (CL) has emerged as a pivotal paradigm to enable large language models (LLMs) to dynamically adapt to evolving knowledge an
arXiv:2608.08459v1 Announce Type: cross Abstract: Practical AI systems increasingly need to turn long, heterogeneous documents into queryable relational databases, not isolated spreadsheets. In domain
Claude's watermark probably doesn't work how you think. As the CTO of GPTZero, I'll explain how Anthropic, Google and OpenAI are building text watermarking in this brief explainer and whether it can b
arXiv:2608.09898v1 Announce Type: new Abstract: Test-time scaling often uses an external verifier, such as compilers and test cases in coding or trained value functions in robotics applications, to ob
arXiv:2608.08061v1 Announce Type: new Abstract: The key question in moral judgement is not simply whether someone chooses the 'right' answer, but how they decide what matters most when moral principle
arXiv:2608.07693v1 Announce Type: cross Abstract: Generative traffic video forecasting aims to synthesize long-horizon, temporally coherent future videos of traffic scenes from a short observation his
arXiv:2608.07476v1 Announce Type: new Abstract: We develop a formal framework for constructing canonical interpretations from plural structure theories. A structure theory is a triple T = ({Sigma}, A,
arXiv:2608.07532v1 Announce Type: new Abstract: Modern agentic AI systems combine multiple large language model agents with heterogeneous skills, yet most architectures either fix communication in adv
arXiv:2602.17902v2 Announce Type: replace Abstract: Large language models (LLMs) can plan scientific workflows and generate code, but these capabilities do not specify how scientific state is validate
arXiv:2510.21891v2 Announce Type: replace-cross Abstract: To deploy large language models (LLMs) in high-stakes application domains that require substantively accurate responses to open-ended prompts,
arXiv:2608.09273v1 Announce Type: new Abstract: LLMs have demonstrated strong capabilities in code generation and automated program repair, but migrating an entire repository rarely produces a runnabl
arXiv:2608.07627v1 Announce Type: new Abstract: Hospitals are racing to embed AI, while coping with the surge in adaptation of the technology in other industries, into the triage management, documenta
arXiv:2608.05235v1 Announce Type: cross Abstract: Research agents increasingly conduct multi-round machine-learning experiments in industrial recommendation settings and retain the resulting trajector
arXiv:2608.09925v1 Announce Type: cross Abstract: Large language models are increasingly being deployed in governmental settings, yet few existing evaluation frameworks jointly reflect the values of p
arXiv:2608.07511v1 Announce Type: cross Abstract: Background. Effective clinical practice relies heavily on the socio-communicative skills of medical professionals. Large language models (LLMs) have b
arXiv:2608.08069v1 Announce Type: cross Abstract: Foundation models are increasingly reused as software components, making model selection a critical software-engineering decision. Current model hubs
Laid off then my partner of 10 years said he's leaving, have to move, etc... I will post the r/hardwareswap link when I make it. I'm willing to add some incentive for r/LocalLLaMA folks. I will also a
arXiv:2608.08210v1 Announce Type: new Abstract: Collaborative dialogue can end with apparent agreement while participants still differ on goals, assumptions, or execution plans, creating an extbf{illu
Introducing ExtractBench, the most comprehensive benchmark for information extraction from complex enterprise documents. The latest models are pushing the frontier of coding and knowledge work, but su
Introducing 𝗘𝘅𝘁𝗿𝗮𝗰𝘁𝗕𝗲𝗻𝗰𝗵: the most comprehensive benchmark for information extraction from complex enterprise documents. Our applied research team tested: 14 systems — frontier VLMs, coding agents, ex
arXiv:2603.07822v2 Announce Type: replace Abstract: Effective human-robot collaboration in open-world environments requires joint planning under uncertainty about the task, the environment, and the hu
arXiv:2608.07547v1 Announce Type: cross Abstract: Indoor scene layout generation is a challenging task in interior design. Existing methods often oversimplify the task by reducing room conditions to c
arXiv:2510.20739v2 Announce Type: replace-cross Abstract: Program analysis tools often produce large volumes of candidate vulnerability reports that require costly manual review, creating a practical
arXiv:2608.09588v1 Announce Type: new Abstract: Traditional Text-to-SQL research and benchmarks assume a known target database, overlooking settings in which a query must be routed within a large, het
arXiv:2608.09818v1 Announce Type: cross Abstract: Reliable medical image understanding requires models to connect clinical language and visual reasoning with pixel-level grounding. Yet medical vision-
arXiv:2601.15394v2 Announce Type: replace Abstract: Knowledge Distillation (KD) is increasingly adopted to transfer capabilities from large language models to smaller ones, offering significant improv
arXiv:2608.09251v1 Announce Type: cross Abstract: Large language model-based multi-agent systems have recently shown strong potential for complex, long-horizon tasks. However, existing methods mainly
arXiv:2608.07993v1 Announce Type: new Abstract: Human motion-text retrieval provides a rigorous means of assessing cross-modal alignment. Prevailing benchmarks are dominated by homogeneous indoor moti
arXiv:2608.09805v1 Announce Type: cross Abstract: Exploration has been a focus of reinforcement learning research for a long time. Recently, there has been growing evidence that it is also an importan
arXiv:2608.09551v1 Announce Type: new Abstract: In the era of large language models (LLMs), attackers often manipulate natural language to elicit unsafe or harmful outputs, creating a new natural lang
arXiv:2608.07478v1 Announce Type: cross Abstract: India's 22 official languages create a critical accessibility barrier: the majority of medical documentation exists exclusively in English, yet the pa
arXiv:2608.09526v1 Announce Type: cross Abstract: Real-world cyberattacks often require sustained progress across multiple hosts and network segments, making multi-hop cyber ranges essential infrastru
leaked Super specs have the 5070 Ti and 5080 going 16GB to 24GB and the 5070 to 18GB, thanks to the new 3GB GDDR7 modules. 24GB on a Ti-class card is actually the number people here have been waiting
arXiv:2603.22213v2 Announce Type: replace-cross Abstract: While large language models (LLMs) are pretrained on massive amounts of data, their knowledge coverage remains incomplete in specialized, data
arXiv:2608.09524v1 Announce Type: cross Abstract: Incident response planning is critical for restoring compromised software systems after cyberattacks. Common practice relies on expert-driven playbook
arXiv:2603.02637v2 Announce Type: replace-cross Abstract: Modern machine learning (ML) workloads increasingly rely on GPUs, yet achieving high end-to-end performance remains challenging due to depende
arXiv:2608.07641v1 Announce Type: new Abstract: The rapid advancement of large language models has transformed survey writing from a months-long manual effort into an automated process. As generation
arXiv:2608.00143v2 Announce Type: replace-cross Abstract: Automated attack chain generation is critical for modern cybersecurity, yet manual construction fails to scale as adversary behaviors expand.
arXiv:2608.09706v1 Announce Type: cross Abstract: Large language models can write parametric CAD programs from a natural-language description (text-to-CAD generation), but a single sample is often wro
arXiv:2608.08113v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting has become the dominant paradigm for eliciting reasoning in Large Language Models (LLMs), yet it creates substantial co
arXiv:2608.08512v1 Announce Type: new Abstract: Evolving documents, such as laws, tax codes, and software documentation, are amended, replaced, and sometimes reverted over time, so a question has diff
arXiv:2608.08446v1 Announce Type: new Abstract: Personalized generation systems retrieve user history by request--memory relevance and inject it into the model context. Yet relevant history may concer