Search: “llm”

arXiv:2609.10464v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architecture (JEPA) world models learn a compact latent representation of the world that supports prediction and planning,

arXiv:2609.06647v1 Announce Type: new Abstract: Although professional workflows leverage large language models widely, the interpretation for auditing unconstrained free-text generation is usually int

arXiv:2609.09233v1 Announce Type: cross Abstract: How can language model agents effectively leverage libraries of reusable knowledge to solve long-horizon tasks? Recent work has increasingly focused o

arXiv:2609.08226v1 Announce Type: new Abstract: Temporal graph learning models the evolution of dynamic systems, where both structural interactions and semantic states change over time. However, exist

arXiv:2609.05920v1 Announce Type: cross Abstract: Agent Skills combine instructions with files, packages, tools, models, and services, so operational identity can exceed a signed directory. Recursive

arXiv:2609.05591v1 Announce Type: cross Abstract: Safety evaluations typically focus on individual agents, but interacting agents can spread harmful information and influence the environment in which

arXiv:2609.07675v1 Announce Type: cross Abstract: Transaction-local controls answer whether one financial request may proceed, but market behavior can be distributed across messages, agents, assets, a

Another banger paper from Google. If you build memory for long-horizon agents, this one is worth your time. (bookmark it) Really nice to see how knowledge graphs are being explored in creative ways fo

arXiv:2609.06779v1 Announce Type: new Abstract: Drug repurposing aims to identify new therapeutic uses for existing compounds and, compared with de novo drug discovery, offers a faster and more cost-e

arXiv:2609.06823v1 Announce Type: new Abstract: The next generation of artificial intelligence systems will likely be natively temporal and multimodal in both inputs and outputs: able to converse, per

arXiv:2606.15277v2 Announce Type: replace-cross Abstract: Graph-based recommendation models effectively capture high-order collaborative signals from user--item interaction graphs. Federated learning

arXiv:2604.05819v2 Announce Type: replace Abstract: Interpreting the decisions of complex computer vision models is crucial to establish trust and accountability, especially in safety-critical domains

arXiv:2609.06116v1 Announce Type: cross Abstract: In the field of UI design, Scalable Vector Graphics (SVG) is widely used as a design medium. However, traditional SVG editing techniques have high ent

arXiv:2609.07135v1 Announce Type: new Abstract: An embodied kitchen assistant must do more than recognize food in isolated frames. It must track ingredient states over time and integrate visual observ

arXiv:2606.14199v2 Announce Type: replace-cross Abstract: Large language models are increasingly deployed as human simulators for interactive evaluation and social simulation. Yet helpfulness-driven p

arXiv:2609.07655v1 Announce Type: new Abstract: Closed-loop AI scientists can generate candidate designs at low marginal computational cost, whereas reliable feedback may require wet-lab synthesis, ch

arXiv:2609.07916v1 Announce Type: new Abstract: Images are important tools in various sciences. Despite the development of photo-taking tools, creating clear and image without noise remains challengin

https://github.com/paulknysh/raggy A lightweight CLI tool for Retrieval-Augmented Generation (RAG) over local documents built with Ollama. Hybrid database (vector + BM25 index) and embedding generatio

I've been running Claude Code as my daily driver and wanted Ollama models in the loop without giving up the harness. So I built gremlord, a small Go binary that points the unmodified claude binary at

arXiv:2609.08444v1 Announce Type: new Abstract: Large language models (LLMs) and vision-language models (VLMs) have significantly advanced zero-shot task planning for embodied agents. However, most LL

arXiv:2609.05594v1 Announce Type: new Abstract: Diverse and simulation-ready indoor scenes are essential for interactive entertainment and embodied AI, yet their scalable generation remains challengin

arXiv:2609.07394v1 Announce Type: new Abstract: Anticipating whether a person will interact from one's own perspective is a highly intuitive task for humans, that relies on a combination of cues. We i

arXiv:2609.08342v1 Announce Type: new Abstract: World models take multimodal inputs like text, photos, and diagrams to generate dynamic scenes in accordance with the laws of physics, thus opening a co

When building consumer-facing generative AI applications, balancing high generation quality with fast response times across diverse media types, can be challenging. KDDI, a major telecommunications ca

Pathway's Baby Dragon Hatchling (BDH) is a brain-inspired, post-transformer architecture that reasons in latent space instead of emitting chain-of-thought tokens. See how Pathway develops and scales B

arXiv:2609.04303v1 Announce Type: cross Abstract: Information abstraction, which groups strategically similar private states into a tractable number of buckets, is essential for scaling game-solving a

arXiv:2609.04913v1 Announce Type: cross Abstract: Automotive infotainment validation still relies on manual testing, slow, costly, and incompatible with agile releases and OTA updates. Scripted automa

arXiv:2609.04651v1 Announce Type: new Abstract: This paper studies adaptive recommendation under intent drift, where feedback from each recommendation outcome can reveal whether the relational evidenc

arXiv:2609.04222v1 Announce Type: cross Abstract: We present GEPARD (Generative, Prosody-aware, Autoregressive text-to-speech model for Realtime Dialogue), a streaming text-to-speech model for real-ti

arXiv:2609.04442v1 Announce Type: cross Abstract: Large language models deployed in high-stakes settings frequently generate plausible but ungrounded claims. Standard retrieval-augmented generation (R

arXiv:2609.04564v1 Announce Type: new Abstract: Self-driving laboratories (SDLs) combine automated experimentation with adaptive decision-making to accelerate scientific discovery. Their operation nev

arXiv:2609.04835v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used not only to retrieve information, but to answer questions, explain, teach, and support inquiry. In su

arXiv:2609.05335v1 Announce Type: cross Abstract: Public vulnerability databases collect rich information about known software flaws, including their weakness types, affected components, and related p

⚠️ The most important question hardly anyone is asking is whether Jensen meant 100K+ GPUs, or 100k+ NVLink72 server racks (which contain 72 Blackwell GPUs). ⚠️ From his wording, it sure looks like the

Been posting individual pieces of RunAnywhere for months. Here's the whole thing in one place. RunAnywhere SDKs is a complete inference suite for any dev who wants to run AI on the user's device. ->8

While we see for frontier models similar scores among famous coding benchmarks, across: DeepSWE, Terminal-Bench, LiveCodeBench, Code-Arena ELO. Here are in my opinion some next level benchmarks that r

Sad to see Jensen claim that AGI has arrived, with no evidence and no definitions. I would urge him to read http://agidefinition.AI by @hendrycks, @Yoshua_Bengio & many others (including myself), and

Anthropic says its first Fermat runs failed not on math, but because dozens of Claude agents lost track of shared project state. They only succeeded after moving to Prove2Me's DAG of statements and pr

I just want to use paperless-ai and be able to ask questions relative to it. Bonus points if I could use it with home assistant but that's not the focus. I just can't see needing a 32 GB VRAM GPU for

Hi, I am thinking about putting some money / time into my local ai learning path and 'cleared' my attic where I found the following hardware. 3 x NUC11 (Core i5 1145G7 / 2,6 GHz, 64 GB RAM DDR4 2666MH

so does this digital fly have the memory of the real fly that was scanned or what I’ve successfully run the full retained MaleCNS v1.0 fruit fly connectome, all 166,700 neurons, inside Minecraft, with

arXiv:2609.03884v1 Announce Type: cross Abstract: Modern AI agent harnesses expose lifecycle hooks that bind shell commands to runtime events such as session start, tool calls, and file edits. These c

arXiv:2609.04170v1 Announce Type: new Abstract: Multi-agent AI science ecosystems rely on agents possessing tools that allow them to communicate, coordinate, and build on each other's work. Yet this s

arXiv:2609.03621v1 Announce Type: new Abstract: Making science computable requires representations of both scientific knowledge and the physical world in which scientific claims are tested. A computab

This research details an agentic framework that automatically generates custom GPU kernels and rigorously validates them. By integrating automated synthesis and thorough performance testing, the syste

arXiv:2609.03502v1 Announce Type: cross Abstract: In low-resource settings, deploying TTS typically requires choosing between a large voice-cloning model with costly inference or a compact fixed-voice