Search: “agents”

arXiv:2608.10796v1 Announce Type: new Abstract: Understanding both expressed and evoked emotions is critical for multimodal large language models (MLLMs) to achieve comprehensive affect-aware interact

arXiv:2608.10805v1 Announce Type: cross Abstract: Wavelet convolution (WTConv) has emerged as an increasingly popular drop-in replacement for standard convolutions, expanding a network's receptive fie

arXiv:2608.10444v1 Announce Type: cross Abstract: Large language models (LLMs) have made substantial progress on reasoning tasks that require increasingly long and complex inferential chains. This pro

arXiv:2608.10886v1 Announce Type: new Abstract: Robots operating in human environments need memories that capture not only what objects exist and where, but also how people use them over time and how

Victoria Song / The Verge: Google unveils the 399 Pixel Watch 5 with a satin pyrite case finish, offline Gemini, proactive AI suggestions, better GPS maps, and insulin resistance trends — The 399 Goog

arXiv:2608.10393v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong capabilities in controlling robots across diverse manipulation tasks. However, their adversarial r

arXiv:2506.03922v4 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated significant potential to advance a broad range of domains. However, current benchma

arXiv:2608.11051v1 Announce Type: new Abstract: As robots increasingly operate in human-populated environments, anticipating human intentions is essential for enabling proactive and socially aware beh

Sometimes you have tasks that are outside of your expertise and the idea is this workflow automation could be leveraged to manage to have local AI figure it out using research from his workflow gather

imo GDPVal is probably the most important benchmark, it measures the performance of models on real world tasks Big leap in performance here to top it at a great price, congrats to @SpaceXAI team & loo

arXiv:2608.10635v1 Announce Type: cross Abstract: Medical Vision-Language Models (Med-VLMs) excel at verbalizing visual content, yet precise visual perception, segmentation, and grounding remain chall

arXiv:2608.10050v1 Announce Type: new Abstract: Small and medium-sized businesses need timely financial guidance, yet historical accounting logs record self-selected and often co-occurring business ch

arXiv:2608.10729v1 Announce Type: cross Abstract: Foundation models can improve their outputs through a self-refinement process driven by external feedback. In this process, the model is embedded in a

arXiv:2608.10908v1 Announce Type: cross Abstract: As generative multimedia evolves from static image synthesis to complex, interleaved visual narratives, a foundational bottleneck has emerged: the jud

arXiv:2608.10483v1 Announce Type: new Abstract: Double perovskites (DPs) offer broad compositional tunability, but predicting the space groups (SGs) of stable structures remains difficult because avai

arXiv:2608.10126v1 Announce Type: cross Abstract: Reinforcement Learning from Human Feedback (RLHF) aggregates heterogeneous preferences into a single reward model, assuming preference homogeneity. Wh

arXiv:2608.11066v1 Announce Type: cross Abstract: We prove inference-time quantum coordination advantages for specified AI state-tracking tasks. A solver compresses semantic history into a future-acce

Qwen3.8-Max is live on Together AI on day zero. Proud to have supported early testing alongside @Alibaba_Qwen, @vllm_project, and Inferact to get day-zero support live. We’re continuing to optimize pe

arXiv:2608.11017v1 Announce Type: cross Abstract: Long-horizon egocentric video is a rich substrate for wearable AI assistants, but object-centric questions such as where an item was moved, when it la

arXiv:2608.10970v1 Announce Type: cross Abstract: Recent advances in Large Language Models (LLMs) have demonstrated strong capabilities in generating semantically relevant concepts and relations, maki

arXiv:2608.10524v1 Announce Type: cross Abstract: Driven by the rapid advancement of vision-language representation learning, Text-based Image Retrieval (TBIR) has made notable progress. However, exis

arXiv:2608.11152v1 Announce Type: cross Abstract: Modern reinforcement learning (RL) post-training pipelines for large language models (LLMs) increasingly combine rollout workloads across multiple dom

Alibaba released the open‑weights Qwen3.8‑2.4T‑A95B (Qwen3.8‑Max), a fine‑grained mixture‑of‑experts model with 2.4 trillion parameters, hybrid full‑ and linear‑attention, a one‑million‑token context

SPACEXAI: Grok 4.6 leads on the two strongest knowledge-work / real-world productivity benchmarks (GDPVal-AA and AA-Briefcase) and on the legal benchmark, while remaining highly competitive on coding-

arXiv:2608.10949v1 Announce Type: cross Abstract: Streaming video understanding requires multimodal large language models (MLLMs) to preserve relevant evidence from continuously evolving streams under

The most dangerous document extraction failure isn't a wrong value. It's a missing row that looks like nothing is wrong. We released ExtractBench yesterday: 370 enterprise docs, 14 systems. The hardes

arXiv:2608.10327v1 Announce Type: new Abstract: Can AI systems be aligned to human values? The popularization of large language models (LLMs) and multi-modal foundation models has seen a rise in harms

Twitch users can now opt out of allowing their content to be used to train Amazon's generative AI models. Opting out means that 'your streams, VODs, clips, stream chats, and pictures and text on your

arXiv:2608.09942v1 Announce Type: cross Abstract: It is widely assumed that chain-of-thought (CoT) prompting universally improves LLM reasoning. We investigate this through the conceptual framework of

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

A few things right off the bat: it reasons very efficiently. Like Grok 4.5 levels of efficient thinking it quantizes very well. My first few tests with iq3_xxs were better than Qwen/Gemma behaved at t

arXiv:2607.28432v2 Announce Type: replace Abstract: Intelligence is commonly understood as the ability to acquire and apply knowledge, adapt to unfamiliar situations and solve new problems. Large lang

arXiv:2603.00077v3 Announce Type: replace-cross Abstract: Rubric-based LLM judges have become indispensable for evaluating and optimizing systems on non-verifiable tasks, where success cannot be reduc

arXiv:2608.07584v1 Announce Type: new Abstract: Vision-language models (VLMs) have made rapid progress in visual perception and increasingly support real-world tasks that depend on images. Many such t

arXiv:2608.07481v1 Announce Type: cross Abstract: This paper investigates whether one large language model can approximate the humor preferences of another in a controlled Cards Against Humanity-style

arXiv:2608.09333v1 Announce Type: new Abstract: Large-scale language models for autonomous driving enable enhanced global understanding and long-horizon planning. However, when deployed in isolated ve

arXiv:2608.09542v1 Announce Type: cross Abstract: Large reasoning models (LRMs) achieve remarkable success on complex tasks but remain vulnerable to harmful prompts that induce unsafe outputs. Recent

arXiv:2608.09762v1 Announce Type: new Abstract: Real-world online reinforcement learning (RL) provides a promising approach for training robotic manipulation policies directly in the physical world, a

arXiv:2608.09024v1 Announce Type: new Abstract: Emergency-department (ED) triage requires clinicians to rapidly identify patients who need immediate attention, determine who can safely wait, and prior

arXiv:2608.07480v1 Announce Type: new Abstract: Active inference has emerged as a principled framework for modeling adaptive behavior by balancing goal-directed action with uncertainty reduction. It h

arXiv:2608.07497v1 Announce Type: cross Abstract: Conversational learner simulations are valuable tools for testing learning theories, evaluating instructional materials and automated tutors, or power

ExtractBench is one of the most comprehensive benchmarks for real-world document extraction. ✅ It covers 4869 pages, across 67 document types, spanning 8 real-world domains: finance, energy, gov, auto

arXiv:2608.09474v1 Announce Type: new Abstract: Text-based person anomaly search requires retrieving real-world pedestrian images from detailed natural-language descriptions using models trained prima

arXiv:2608.08445v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) is widely regarded as a novel paradigm born from the limitations of large language models (LLMs)--a mechanism to gr

arXiv:2608.09842v1 Announce Type: new Abstract: Recent document parsers achieve table TEDS scores above 93 on OmniDocBench v1.6, yet community feedback and our audit reveal persistent failures on comp

From @sequoia's own your intelligence event. We're starting to see a new category of company emerge, the Full-Stack AI company, where innovation happens at both the product and intelligence layer. Tha