Knowledge catalogue
Cursor has introduced a new feature that allows its AI to respond by generating interactive canvases, enabling users to visually represent information beyond standard text responses. Users can prompt
arXiv:2603.07083v2 Announce Type: replace Abstract: Model-based reinforcement learning (MBRL) agents operating in high-dimensional observation spaces, such as Dreamer, rely on learning abstract repres
arXiv:2604.12474v1 Announce Type: cross Abstract: In many robotic tasks, agents must traverse a sequence of spatial regions to complete a mission. Such problems are inherently mixed discrete-continuou
Moss is a YC-backed high-performance runtime for real-time semantic search that delivers sub-10ms lookups, instant index updates, and zero infrastructure overhead, running where the agent lives — clou
If it can’t parse, it can’t perform. ❌ Reliable document understanding is fundamental to enterprise-grade #AgenticAutomation. We're excited to see the release of ParseBench, a new open-source benchmar
arXiv:2604.12034v1 Announce Type: new Abstract: Retrieval-Augmented Generation remains the dominant pattern for giving LLMs persistent memory, but a visible cluster of personal wiki-style memory archi
arXiv:2604.11943v1 Announce Type: cross Abstract: An OS kernel that runs LLM inference internally can read logit distributions before any text is generated -- and act on them as a governance primitive
arXiv:2511.17097v2 Announce Type: replace Abstract: Vision-Language Navigation requires agents to act coherently over long horizons by understanding not only local visual context but also how far they
proud of this launch from a strong team. dedicated hardware for high throughput, low cost search building for the new era of recommenders and agents Dedicated Read Nodes are now generally available. P
arXiv:2604.12371v1 Announce Type: new Abstract: We study typographic prompt injection attacks on vision-language models (VLMs), where adversarial text is rendered as images to bypass safety mechanisms
arXiv:2604.12911v1 Announce Type: cross Abstract: Multilingual benchmarks guide the development of frontier models. Yet multilingual evaluations reported by frontier models are structured similar to p
arXiv:2604.12350v1 Announce Type: cross Abstract: Molecular property optimization is central to drug discovery, yet many deep learning methods rely on black-box scoring and offer limited control over
arXiv:2508.04282v3 Announce Type: replace Abstract: Recent benchmarks for memory-augmented reinforcement learning (RL) have introduced partially observable Markov decision process (POMDP) environments
arXiv:2604.12232v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed across diverse domains, yet their vulnerability to jailbreak attacks, where adversarial inputs
This Reddit post contrasts the r/ChatGPT community's tendency to focus on AI failures and viral screenshots with a more pragmatic user base building real workflows on RunLobster, a managed cloud platf
Databricks outlines eight key AI and data trends expected to transform financial services in 2026, likely covering advancements in generative AI, real-time data processing, machine learning for risk m
arXiv:2604.10579v1 Announce Type: cross Abstract: Despite the recent success of modern imitation learning methods in robot manipulation, their performance is often constrained by geometric variations
AI development is shifting toward fully integrated, agent-enabled applications, with major platforms like Anthropic's Claude and OpenAI
arXiv:2604.10031v1 Announce Type: cross Abstract: Theory of Mind (ToM), the ability to attribute mental states to others, is a hallmark of social intelligence. While large language models (LLMs) demon
arXiv:2604.11322v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated impressive capabilities in utilizing external tools. In practice, however, LLMs are often exposed to to
arXiv:2604.09741v1 Announce Type: cross Abstract: For large language models deployed through black-box APIs, recurring inference costs often exceed one-time training costs. This motivates composed age
arXiv:2601.05505v2 Announce Type: replace Abstract: The stateless architecture of Large Language Models inherently lacks the mechanism to preserve dynamic context, compelling agents to redundantly rep
Had a fantastic time at the @aiDotEngineer Europe conference in London last week. There was a lot of good coverage of people's emerging approaches for working with AI coding agents. A couple of the st
Konstantin Kakaes / Quanta Magazine: How some mathematicians are exploring ways to incorporate LLM models into their research without losing direct experience with mathematical understanding — Those c
However, most alignment research is not very crisp and requires research taste when evaluating. This is why we chose to point the AAR at this scalable oversight problem! Progress would let AARs work o
arXiv:2604.05165v2 Announce Type: replace Abstract: Reconfigurable Intelligent Surfaces (RIS) has a potential to engineer smart radio environments for next-generation millimeter-wave (mmWave) networks
arXiv:2604.09998v1 Announce Type: cross Abstract: Large language models (LLMs) have recently emerged as promising tools for augmenting Security Operations Center (SOC) workflows, with vendors increasi
arXiv:2604.11004v1 Announce Type: cross Abstract: In this work, we introduce a new perspective on comparative image assessment by representing an image pair as a structured composition of its regions.
ParseBench is the most comprehensive OCR benchmark for real-world enterprise documents: financial filings, contracts, insurance documents, and more. We evaluate across 5 dimensions that are present am
arXiv:2604.09675v1 Announce Type: cross Abstract: Outbound AI calling systems must distinguish voicemail greetings from live human answers in real time to avoid wasted agent interactions and dropped c
arXiv:2604.11759v1 Announce Type: new Abstract: Organizational knowledge used by AI agents typically lacks epistemic structure: retrieval systems surface semantically relevant content without distingu
arXiv:2602.03402v3 Announce Type: replace Abstract: Vision language models (VLMs) extend the reasoning capabilities of large language models (LLMs) to cross-modal settings, yet remain highly vulnerabl
Over 80% of enterprise data lives in unstructured form — PDFs, emails, reports, regulatory filings. Most of the time, such sources contain critical business information, yet they remain difficult to a
arXiv:2505.17012v3 Announce Type: replace-cross Abstract: Existing evaluations of multimodal large language models (MLLMs) on spatial intelligence are typically fragmented and limited in scope. In thi
Cursor offers a pre-built automation template in its marketplace that helps developers investigate Sentry issues more efficiently. The template, accessible at cursor.com/marketplace/automations/invest
arXiv:2604.11757v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for building general-purpose robotic agents. However, the VLA landsc
arXiv:2604.11184v1 Announce Type: cross Abstract: Context: Software engineering (SE) researchers increasingly study Generative AI (GenAI) while also incorporating it into their own research practices.
For years, the promise of “no-code” artificial intelligence has felt a bit like a “some assembly required” IKEA desk — sure, you aren’t sawing the wood yourself, but you’re trying to decipher how to a
arXiv:2604.10733v1 Announce Type: cross Abstract: Large language models increasingly serve as conversational agents that adopt personas and role-play characters at user request. This capability, while
arXiv:2604.08595v1 Announce Type: cross Abstract: Existing evaluation methods for LLM-based AI systems, such as LLM-as-a-Judge, verdict systems, and NLI, do not always align well with human assessment
Benchmarked @DJLougen ’s Ornstein-27B-v2 Q6_K on my RTX 3090 using hermes-bench, my new open-source benchmarking UI for local LLMs and Hermes agents. Ornstein is a Qwen 3.5 27B fine-tune trained on re
arXiv:2511.01383v2 Announce Type: replace Abstract: Accurate point-wise velocity estimation in 3D is crucial for robot interaction with non-rigid dynamic agents, enabling robust performance in path pl
Stanford University researchers today released their highly anticipated 2026 AI Index Report, revealing a global landscape where artificial intelligence technology is being adopted at record-breaking
arXiv:2604.08846v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have been shown to be vulnerable to malicious queries that can elicit unsafe responses. Recent work uses prom
arXiv:2604.08603v1 Announce Type: new Abstract: Existing LLM-based agent systems share a common architectural failure: they answer from the unrestricted knowledge space without first simulating how ac
arXiv:2604.04089v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate code rapidly but remain unreliable for scientific algorithms whose correctness depends on structural
arXiv:2604.09222v1 Announce Type: cross Abstract: Audio large language models (ALLMs) enable rich speech-text interaction, but they also introduce jailbreak vulnerabilities in the audio modality. Exis
I am catching glimpses in my feed that there is a backlash against Mythos as 'marketing hype,' and it is a little confusing. I don't think anyone who has used the latest agentic coding tools, would th
arXiv:2604.09544v1 Announce Type: cross Abstract: Large language models (LLMs) undergo alignment training to avoid harmful behaviors, yet the resulting safeguards remain brittle: jailbreaks routinely
arXiv:2604.09024v1 Announce Type: cross Abstract: Multi-modal large language models (MLLMs) have emerged as powerful tools for analyzing Internet-scale image data, offering significant benefits but al
arXiv:2604.08952v1 Announce Type: new Abstract: Document Question Answering (DQA) involves generating answers from a document based on a user's query, representing a key task in document understanding
arXiv:2411.10636v2 Announce Type: replace-cross Abstract: In this study, we investigate extrinsic gender bias in Bangla pretrained language models, a largely underexplored area in low-resource languag
arXiv:2604.09253v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are powerful but remain vulnerable to multimodal jailbreak attacks. Existing attacks mainly rely on either explicit visu
arXiv:2604.09452v1 Announce Type: cross Abstract: Safety guarantees are a prerequisite to the deployment of reinforcement learning (RL) agents in safety-critical tasks. Often, deployment environments
arXiv:2604.08555v1 Announce Type: new Abstract: Physician-physician discussions of patient cases represent a rich source of clinical knowledge and reasoning that could feed AI agents to enrich and eve
The entire team put a lot of effort into this benchmark. Document parsing and OCR certainly isn't solved, but now it is a bit easier to measure 🦙 We’re open sourcing the first document OCR benchmark f
arXiv:2604.09368v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly deployed as scalable user simulators for recommender system evaluation. Yet existing simulators per
arXiv:2604.08780v1 Announce Type: cross Abstract: World models promise a paradigm shift in robotics, where an agent learns the underlying physics of its environment once to enable efficient planning a
A Reddit user exploring Ollama Cloud noted that, at the time of their post, only the Kimi model supported image (vision/multimodal) inputs among the available cloud models. Kimi K2.5 is a native multi
Violence is not the answer. But maybe boycotts are? 🚨 NOW: The FBI is RAIDING the home of a 20-year-old man who threw a molotov cocktail at the home of OpenAI CEO Sam Altman Over a DOZEN federal agent