Knowledge catalogue
arXiv:2605.27929v1 Announce Type: cross Abstract: Active sensing links behavior and learning through an action-perception loop: actions determine the observations used to update internal predictive mo
arXiv:2605.28037v1 Announce Type: new Abstract: Prompt-based personality control is a key technique for designing large language model (LLM) dialogue agents that behave consistently across social cont
arXiv:2605.28498v1 Announce Type: cross Abstract: Conversational artificial intelligence (AI) provides an efficient and convenient gateway to information access. However, it can cause overreliance whe
AI factories are token factories, converting power into intelligence in real time. And as agentic AI scales and autonomous, always-on special agents are deployed in the enterprise, performance per wat
arXiv:2605.24516v1 Announce Type: cross Abstract: Mixed-motive scenarios are ubiquitous in real-world multi-agent interactions, where self-interested agents often defect for immediate rewards, overloo
arXiv:2602.05448v4 Announce Type: replace Abstract: Selecting the top m from n items via expensive k-wise comparisons is central to settings ranging from LLM-based document reranking to crowdsourced e
arXiv:2605.24999v1 Announce Type: cross Abstract: An agent must act on the situation before it, learn what it cannot yet represent, and model other agents well enough to coordinate. These faculties ar
arXiv:2605.25376v1 Announce Type: cross Abstract: Observability tells operators when an agent is slow. KYA tells operators when an agent is wrong, drifting, leaking, or quietly going rogue. We present
arXiv:2605.24048v1 Announce Type: cross Abstract: Multi-AI collaboration, such as ensembling or debating large language models (LLMs), is a promising paradigm for aggregating information and boosting
arXiv:2602.11439v2 Announce Type: replace Abstract: Strategic classification studies the problem where self-interested individuals or agents manipulate their response to obtain favorable decision outc
arXiv:2605.25535v1 Announce Type: new Abstract: Existing large language model (LLM) based memory systems apply universal, static policies that overlook a fundamental reality: the contexts that are wor
arXiv:2605.24366v1 Announce Type: new Abstract: Large Language Models (LLMs) have been widely adopted in conversational applications. However, their reliance on parametric knowledge limits reliability
arXiv:2601.22324v2 Announce Type: replace Abstract: Modern clinical practice relies on evidence-based guidelines implemented as compact scoring systems composed of a small number of interpretable deci
arXiv:2605.21082v1 Announce Type: new Abstract: Large Language Model (LLM) based agents have demonstrated proficiency in multi-step interactions with graphical user interfaces (GUIs). While most resea
arXiv:2605.21984v1 Announce Type: cross Abstract: Static 'human data' faces inherent limitations: it is expensive to scale and bounded by the knowledge of its creators. Continuous learning from 'exper
Grok progress Grok Imagine Agent Mode is now available on Grok iOS app With Agent Mode, you can generate: • Consistent characters across generations • Multiple scenes with the same character • Differe
Open-source AI agents are changing software development, empowering both developers and citizen builders alike in a domain once reserved for professional engineers. But the influx of agents now spread
arXiv:2603.08403v3 Announce Type: replace Abstract: Long-horizon action-conditioned video generation aims to synthesize temporally coherent videos that follow complex action instructions over extended
He's right. And it has a direct implication for code review that nobody's talking about. Think about why AI cracked coding before almost everything else. Not because code is simple. Because code is ch
Many healthcare organizations report that traditional worklist systems rely on rigid rules that ignore critical context, radiologist specialization, current workload, fatigue levels, and case complexi
arXiv:2605.20272v1 Announce Type: new Abstract: While humans readily generalize abstract concepts to more complex or larger tasks, building Reinforcement Learning (RL) systems with this ability remain
arXiv:2605.19077v1 Announce Type: cross Abstract: Task-oriented dialogue systems -- handling transactions, reservations, and service requests -- require predictable behavior, yet the moderately-sized
arXiv:2605.19328v1 Announce Type: cross Abstract: Recent advances in Vision-Language Models (VLMs) facilitate a new class of embodied AI systems, where these models are integrated into physical platfo
arXiv:2605.18890v1 Announce Type: cross Abstract: The scientific claims drawn from LLM social simulations should be no stronger than the robustness audits that support them. Generative agents bring ne
arXiv:2605.17921v1 Announce Type: new Abstract: Streaming video requires handling dynamic information density under strict latency budgets. Yet, existing methods typically employ static strategies, su
arXiv:2605.17694v1 Announce Type: new Abstract: Power differences shape human communication through well documented socio cognitive effects, including language coordination, pronoun usage, authority b
Join us as a Forward Deployed Engineer! looking for someone to help us bring Hermes agent to the world. if you're a hermes agent power user and want to help others become one as well, hit my dms or em
arXiv:2605.17877v1 Announce Type: new Abstract: A significant hurdle for current LLMs is the execution of complex, multi-stage tasks. Group Relative Policy Optimization (GRPO) has been emerging as a l
arXiv:2605.16671v1 Announce Type: new Abstract: Rapid biodiversity loss underscore the urgency of effective monitoring, yet manual surveys remain resource-intensive. While on-device AI offers a scalab
arXiv:2510.24701v3 Announce Type: replace-cross Abstract: We present Tongyi DeepResearch, an agentic large language model, which is specifically designed for long-horizon, deep information-seeking res
arXiv:2605.15400v1 Announce Type: new Abstract: While AI agents are rapidly advancing from isolated tools to interactive collaborators, data-driven human-machine teaming (HMT) methods remain costly in
arXiv:2605.15665v1 Announce Type: new Abstract: Deploying large language model (LLM)-driven conversational agents in enterprise settings requires prompts that are simultaneously correct at launch and
The first NVIDIA Vera CPUs arrived at three of the world's leading AI labs on Friday — Anthropic in San Francisco, OpenAI in Mission Bay, SpaceXAI in Palo Alto — followed by a delivery to Oracle Cloud
arXiv:2605.14153v1 Announce Type: cross Abstract: Exploitation is not a binary event. It is a ladder of acquiring progressive capabilities, from executing a single buggy line of code to taking full co
Key ideas I picked up at the @LangChain conference this week: 'AI engineering is data science. Look at your data.' — @sh_reya & @HamelHusain 'Data strategy *before* agents.' — @AndrewYNg 'Coding agent
arXiv:2605.12512v1 Announce Type: cross Abstract: Driven by large language models (LLMs), social bot can autonomously engage in local interactions, whose human-like behaviors enable them to evade soci
arXiv:2605.12520v1 Announce Type: cross Abstract: Taxonomy induction is crucial for organizing concepts into explicit and interpretable semantic hierarchies. While existing methods have achieved promi
LangSmith Engine is a phase shift because traces are no longer just records to be manually inspected, they’re now the catalyst for recursive agent self-improvement Engine looks at your traces, finds w
arXiv:2605.11556v1 Announce Type: cross Abstract: Solving complex long-horizon tasks requires strong planning and reasoning capabilities. Although datasets with explicit chain-of-thought (CoT) rationa
arXiv:2605.12460v1 Announce Type: cross Abstract: The continued improvements in language model capability have unlocked their widespread use as drivers of autonomous agents, for example in coding or c
arXiv:2406.12708v3 Announce Type: replace Abstract: Peer review is fundamental to the integrity and advancement of scientific publication. Traditional methods of peer review analyses often rely on exp
arXiv:2605.09045v1 Announce Type: new Abstract: Agentic frameworks are the software layer through which AI agents act in the world. Existing safety methods intervene on the model and therefore remain
Grok Voice is #1! Announcing agentic performance benchmarking for Speech to Speech models on Artificial Analysis. We use 𝜏-Voice to measure tool calling and customer interaction voice agent capabiliti
arXiv:2605.08445v1 Announce Type: new Abstract: AI models are increasingly deployed in live clinical environments where they must perform reliably across complex, high-stakes workflows that standard t
arXiv:2605.08503v1 Announce Type: new Abstract: Interactive narrative tasks require LLMs to sustain a coherent, evolving story while adapting to a user over multiple turns. However, suitable benchmark
arXiv:2505.10872v4 Announce Type: replace-cross Abstract: Robot task planning decomposes human instructions into executable action sequences that enable robots to complete a series of complex tasks. A
arXiv:2605.09730v1 Announce Type: new Abstract: Iterative self-refinement is a popular inference-time reliability technique, but its effectiveness in code-mode tool use depends heavily on the structur
arXiv:2409.13107v3 Announce Type: replace Abstract: Large language model-based (LLM) agents are emerging as a powerful enabler of robust embodied intelligence due to their capability of planning compl
arXiv:2605.10579v1 Announce Type: new Abstract: Training AI agents to proactively assist humans in daily activities, from routine household tasks to urgent safety situations, requires large-scale visu
arXiv:2605.07138v1 Announce Type: new Abstract: Reinforcement learning from verifiable emotion rewards RLVER has produced language models with strong empathetic performance, evaluated on benchmarks th
arXiv:2605.07768v1 Announce Type: cross Abstract: We investigate interactive trajectory planning subject to uncertainty in the decisions of surrounding agents. To control the ego-agent, we aim to firs
arXiv:2605.08007v1 Announce Type: new Abstract: Susceptibilities are a technique for neural network interpretability that studies the response of posterior expectation values of observables to perturb
arXiv:2605.06825v1 Announce Type: new Abstract: Full parameter sharing is standard in cooperative multi-agent reinforcement learning (MARL) for homogeneous agents. Under permutation-symmetric observat
arXiv:2605.07671v1 Announce Type: cross Abstract: Eliciting truthful reports from autonomous agents is a core problem in scalable AI oversight: a principal scores the agent's report using a strictly p
Maybe one of the only moats in 2026 is the context layer. AI improvements mean: ✅ UI/UX might simplify and consolidate. Instead of a lot of fancy buttons/knobs, you need simple, clean interfaces where
Today, we’re thrilled to announce that Gemini 3.1 Flash-Lite, our fastest and most cost-efficient Gemini 3 series model yet, is now generally available. Designed for ultra-low latency, high-volume tas
arXiv:2605.03546v1 Announce Type: cross Abstract: Turning ideas into full software projects from scratch has become a popular use case for language models. Agents are being deployed to seed, maintain,
arXiv:2605.04712v1 Announce Type: new Abstract: In deep reinforcement learning (DRL), an agent is trained from a stream of experience. In a continual learning setting, such agents can suffer from plas
Stories like this is why we built E2B. Watching @genspark_ai go from zero to 250M ARR in 12 months on our infrastructure is one of the best feelings in this job. Their Super Agent does deep research,
arXiv Papers → LLM Artifacts This is how I keep up with AI research now. It's like having access to the most personalized arXiv feed. Automations run everyday to curate papers based a set of rules and