Search: “reasoning”

arXiv:2608.11584v1 Announce Type: new Abstract: Enterprise RAG deployments face a critical reliability gap: while LLMs satisfy 80% of individual constraints, only 26.8% of responses meet all requireme

arXiv:2608.11746v1 Announce Type: cross Abstract: Modern systems are increasingly expected to transfer across tasks not specified during training. What data facilitates generalization in these new, un

Learn how evaluation-driven development, agent harnesses, AI observability, guardrails, and cost-per-outcome metrics move AI agents from pilot to production. The post Evaluation-driven development: Ho

arXiv:2608.11674v1 Announce Type: cross Abstract: On-policy rollout methods such as GRPO are central to post-training of large language models, yet they frequently suffer from training instabilities,

arXiv:2608.11451v1 Announce Type: cross Abstract: Modern end-to-end driving agents can achieve high average performance yet still violate basic traffic rules that a human driver would never miss. The

arXiv:2603.00056v2 Announce Type: replace-cross Abstract: STEM Mental models can play a critical role in assessing students' conceptual understanding of a topic. They not only offer insights into what

arXiv:2608.11660v1 Announce Type: cross Abstract: Large language models (LLMs) achieve remarkable performance across natural language tasks, yet they are trained on static corpora and their knowledge

arXiv:2608.11597v1 Announce Type: cross Abstract: As smart port infrastructures increasingly rely on autonomous maritime devices enabled by the Internet of Things (IoT), ensuring reliable onboard navi

arXiv:2608.11741v1 Announce Type: cross Abstract: The scholarly exegesis of ancient Chinese characters demands integrating visual observation, linguistic analysis, and historical context. However, exi

arXiv:2608.12283v1 Announce Type: cross Abstract: Large language models can extract richer signals from financial news than fixed sentiment lexicons, and recent work has explored feeding such signals

arXiv:2608.11995v1 Announce Type: cross Abstract: The robust treatment of environmental and operational variability (EOV) is an open challenge in population-based structural health monitoring (PBSHM).

arXiv:2608.11624v1 Announce Type: cross Abstract: Persuasion is a core dynamic of natural language communication, shaping how large language models (LLMs) update beliefs, resolve disagreements, and re

Release: llm-gemini 0.33 It's been a while since the last llm-gemini release. This version of the plugin adds support for today's Gemini 3.7 Flash release, plus gemini-3.6-flash, gemini-3.5-flash-lite

arXiv:2608.12045v1 Announce Type: new Abstract: Despite growing interest in weakly supervised video anomaly detection (WSVAD), current methods struggle to bridge the gap between coarse temporal superv

arXiv:2608.11847v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) integrate visual perception with language generation, enabling responses that span image understanding and comple

arXiv:2510.26690v3 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has become a popular technique for parameter-efficient fine-tuning of large language models (LLMs). In many real-world sc

The maximum frame count allowed by the native 'MiniMax H3 Reference to Video' node technically is 1008, even if that's way over the training range of the model, which is 324 frames. But why not try? S

I’m genuinely pretty disappointed with how my Ollama Pro annual subscription turned out. For context, I’m a technology editor and developer, and I had actually used Ollama Pro before. My previous expe

arXiv:2507.22423v3 Announce Type: replace Abstract: To engineer AGI, we should first capture the essence of intelligence in a species-agnostic form that can be evaluated, while being sufficiently gene

On Aug 13 2026, OpenAI announced a preview of its “Ultrafast” mode for the GPT‑5.6 model, called Sol, which claims inference speeds up to 14× faster than current releases. The feature is initially rol

I may have stumbled onto something interesting while trying to figure out a recurring artifact in ChatGPT image generation and editing (maybe applicable to other models as well?). It started with a ve

arXiv:2608.11233v1 Announce Type: cross Abstract: A dense, pretrained language model can be retrofitted with recurrent depth and learn an iterative latent transition that persists after outcome-only a

arXiv:2608.11742v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as a competitive alternative to autoregressive language models, offering the potential for substant

arXiv:2509.13450v3 Announce Type: replace Abstract: We introduce SteeringSafety, a benchmark for evaluating representation steering methods across nine safety perspectives spanning 18 datasets. While

arXiv:2608.11938v1 Announce Type: new Abstract: Sparse voxel reconstruction offers an efficient representation for high-fidelity 3D modeling, yet its geometry is commonly optimized from local photomet

arXiv:2608.11775v1 Announce Type: new Abstract: Gist-based context compression---summarising older conversation history into compact representations---is a common approach in long-horizon language mod

arXiv:2608.12057v1 Announce Type: new Abstract: Feature selection is one of the most important and fundamental tasks in data mining, tackled by a family of methods with an established set of evaluatio

arXiv:2608.12155v1 Announce Type: new Abstract: Vision foundation models have recently emerged as powerful feature extractors for detecting AI-generated images, achieving strong generalization across

When enterprises transition from using simple chat assistants to autonomous, agentic workloads, they quickly run into a hard truth: Agents are prone to inaccurate insights when working with directly r

arXiv:2608.11883v1 Announce Type: new Abstract: Multimodal satellite imagery provides complementary information for Earth Observation, but accurately combining heterogeneous sensors remains challengin

arXiv:2602.14419v2 Announce Type: cross Abstract: This paper reformulates Transformer/Attention mechanisms in Large Language Models (LLMs) through measure theory and frequency analysis, theoretically

arXiv:2608.11403v1 Announce Type: new Abstract: Self-consistency (SC) via majority vote is a widely used way to spend inference-time compute: sample N chains of thought, return the plurality answer. O

arXiv:2608.11715v1 Announce Type: cross Abstract: The reliability of Large Language Models (LLMs) for API calling degrades in multilingual settings. A common failure occurs when a model selects the co

arXiv:2608.12150v1 Announce Type: new Abstract: Standard evaluation of large language models assumes stable model rankings across inference conditions. We challenge this assumption by varying the toke

I've been building an open-source tool for diagnosing world models, the kind that predict future frames from a starting context and a sequence of actions. It compares a rollout against ground truth an

arXiv:2608.11676v1 Announce Type: new Abstract: Heterogeneous multi-agent LLM systems, where agents are powered by different model families, can outperform homogeneous configurations by reducing redun

18 two-word AI prompts I'm kind of obsessed with: 1) now what - great for when you've wrapped up a project or big push and you still have energy and want AI to give you more 2) plz fix - usually accom

In OCP APAC 2026, Tai AMD SVP of compute and enterprise AI said agents don't cut GPU demand but they just pile on a whole extra layer of orchestration, retrieval, and tool-calling work that runs on CP

arXiv:2608.11110v1 Announce Type: new Abstract: When a tool-using agent is given the same task in a different language, does it still take the same steps? Multilingual evaluation rarely asks: it compa

arXiv:2608.10817v1 Announce Type: new Abstract: Zero-shot object-goal navigation (ZSON) in open-vocabulary scenarios is challenging, as it requires a robot to locate an arbitrarily specified object in

arXiv:2608.10600v1 Announce Type: cross Abstract: Skill abstraction---the process of learning reusable and temporally extended behaviors---has emerged as a key paradigm for improving sample efficiency

arXiv:2608.10462v1 Announce Type: new Abstract: Large language models (LLMs) are trained on massive and largely undisclosed corpora that may contain copyrighted or privacy-sensitive content. Data cont

arXiv:2608.10867v1 Announce Type: new Abstract: Gradient-free post-training has emerged as a compelling alternative to gradient-based optimization for large language models (LLMs), but existing approa

arXiv:2608.10120v1 Announce Type: new Abstract: Modern sequence models, from Transformers to State Space Models, have enabled powerful generative modeling across diverse domains, yet they are typicall

North Micro Vision Instruct is a 2.4B-parameter open-weight vision-language model with native-resolution image support, released under the Apache 2.0 license. It is designed as a compact foundation fo

arXiv:2608.10765v1 Announce Type: new Abstract: Recognizing human behavior across levels of abstraction, from atomic actions to long-horizon intentions, requires data annotated along a semantic hierar