Search: “reasoning”

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

DeepSeek V4 Pro 0813 (on OpenRouter) The latest DeepSeek Pro model is now available, via API only. I had to link to OpenRouter because DeepSeek don't have any obvious announcement page for their new m

arXiv:2603.14047v3 Announce Type: replace-cross Abstract: Complex engineered systems require coordinated design choices across heterogeneous components under conflicting objectives and uncertain speci

arXiv:2608.09972v1 Announce Type: cross Abstract: First-generation AI weather models are often reported to underperform at extremes, mostly in reanalysis-based evaluations of deterministic regression

arXiv:2603.25251v2 Announce Type: replace-cross Abstract: Explainable AI (XAI) methods are commonly evaluated using functional correctness metrics, sometimes termed faithfulness or fidelity, which est

arXiv:2608.10366v1 Announce Type: new Abstract: Real-world data science involves long-horizon workflows that span data wrangling, exploration, modeling, visualization, and validation, and require coor

arXiv:2608.10247v1 Announce Type: cross Abstract: Real-world recommendation platforms routinely collect explicit negative feedback such as 1-star reviews, hate-button clicks, distrust between users, a

arXiv:2608.10756v1 Announce Type: cross Abstract: Embodied mobile manipulation requires language, visual observations, three-dimensional scene structure, and action feasibility to be aligned before ex

arXiv:2608.10232v1 Announce Type: cross Abstract: Recent world-action models (WAMs) show that co-training policies with future prediction can provide physical priors for action generation. Building on

arXiv:2608.10668v1 Announce Type: new Abstract: Temporal knowledge graphs are central to many uses of the Semantic Web, but existing completion methods assume the entities, relation names, and timesta

arXiv:2608.10502v1 Announce Type: new Abstract: Persistent memory lets language-model agents reuse information across sessions, but it also makes errors durable: a poisoned, stale, or misattributed re

arXiv:2608.11171v1 Announce Type: cross Abstract: The Workshop on Trustworthy Natural Language Processing (TrustNLP), co-located with major ACL conferences since 2021, has grown from 8 proceedings pap

arXiv:2601.17387v3 Announce Type: replace Abstract: Multilingual speech-text models rely on cross-modal language alignment to transfer knowledge between speech and text, but it remains unclear whether

arXiv:2608.10426v1 Announce Type: new Abstract: Open-vocabulary remote sensing segmentation has recently emerged as a promising paradigm that enables pixel-level recognition of arbitrary categories sp

arXiv:2601.18579v2 Announce Type: replace-cross Abstract: Graph RAG on corpus graphs enhances retrieval by leveraging intermediate node content as contextual clues to uncover unretrieved oracle nodes.

Grok 4.6 is an excellent model. I’ve been using it heavily for the past couple of weeks and it handles everything from simple coding & code review all the way to designing and debugging complex system

arXiv:2608.10330v1 Announce Type: new Abstract: AI agents are increasingly being developed to assist humans in various applications, and Large Language Models and other deep network architectures are

arXiv:2608.10843v1 Announce Type: new Abstract: First-order concept synthesis asks a system to infer one formula that classifies labeled objects consistently across several finite relational structure

arXiv:2602.16481v2 Announce Type: replace Abstract: Causal discovery seeks to uncover causal relations from data, typically represented as causal graphs, and is essential for predicting the effects of

LFM2.5-VL-3B is a multimodal variant of LFM2.5, a family of hybrid models designed for on-device deployment. It builds on LFM2-VL-3B with further mid- and post-training. LFM2.5-VL-3B can process both

arXiv:2608.10273v1 Announce Type: cross Abstract: Deploying large language models (LLMs) for decision support in emergency departments (EDs) faces two major challenges: privacy risks of transmitting p

arXiv:2608.10300v1 Announce Type: new Abstract: Electronic health-record interoperability is a boundary problem: legacy systems, generative models, terminology services, identity systems, and human re

arXiv:2608.11027v1 Announce Type: cross Abstract: Benchmark leaderboards summarize how well a language model performs, but not how its behavior relates to that of other models or changes across genera

arXiv:2608.10827v1 Announce Type: cross Abstract: Medical visual agents can use tools to inspect images and retrieve external knowledge, but indiscriminate tool use may introduce noisy or misleading e

arXiv:2608.10974v1 Announce Type: new Abstract: Scientific papers contain fine-grained records of problem solving: authors mention technical obstacles and methods that were used to address them, often

arXiv:2608.11036v1 Announce Type: new Abstract: Although Whisper models benefit from large-scale multilingual pre-training, their performance on Burmese medical speech remains limited. This work prese

arXiv:2608.09944v1 Announce Type: cross Abstract: Modern web interfaces are increasingly difficult to use with screen readers, particularly when pages update dynamically or hide important structure be

arXiv:2608.10530v1 Announce Type: cross Abstract: Large Language Models (LLMs) have undergone a shift from stateless conversational interfaces to autonomous agents capable of multi-step planning, tool

arXiv:2608.10694v1 Announce Type: cross Abstract: Evolutionary optimization of LLM prompts and agentic programs (e.g., GEPA) is dominated by fitness evaluation: scoring each candidate runs an answerin

arXiv:2608.10021v1 Announce Type: new Abstract: Self-attention models content-dependent interactions between tokens but does not by itself encode token order. Position encoding addresses this limitati

Qwen3.8-2.4T-A95B is now live on Fireworks with Day-0 support! This 2.4T parameter MoE model is built for autonomous agents, heavy coding, large context windows, and is ideal for coding and agentic 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:2608.11030v1 Announce Type: cross Abstract: Patent retrieval and matching based on large language models (LLMs) play a vital role in intellectual property protection. However, due to the complex

arXiv:2608.10692v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as mobile assistants, where a key challenge is leveraging personal information scattered across

arXiv:2608.11075v1 Announce Type: new Abstract: Event cameras capture intensity changes asynchronously with high temporal resolution, requiring novel preprocessing methods for downstream tasks. Unlike

arXiv:2608.09995v1 Announce Type: cross Abstract: Joint demosaicing and denoising is a fundamental step in camera image signal processing, yet remains challenging because different Bayer-like color fi

arXiv:2608.11204v1 Announce Type: cross Abstract: Learning reliable surgical manipulation policies is bottlenecked by the scarcity of action-labeled demonstrations: teleoperated surgical robot (e.g.,

arXiv:2608.10903v1 Announce Type: new Abstract: Reliable clinical deployment of machine learning requires models that know when they are likely to fail, particularly for subgroups underrepresented in

arXiv:2608.10758v1 Announce Type: new Abstract: Vision-language models can describe an image with remarkable accuracy, yet a more fundamental question remains unanswered: what visual information actua

arXiv:2608.11095v1 Announce Type: new Abstract: Agentic coding READMEs like CLAUDE.md grow without bound in real repositories, stopping only when the repository retires or someone rewrites the file wh

Why does CLAUDE.MD keep growing? If you maintain a CLAUDE.md or an AGENTS.md, this one is worth your time. (bookmark it) This work traces why these files grow without bound. Appending an instruction i

arXiv:2608.08743v1 Announce Type: cross Abstract: Reinforcement learning (RL) seeks to optimize sequential decisions to maximize population-level benefits over time. However, when deployed in high-sta

arXiv:2608.09072v1 Announce Type: cross Abstract: Large language model-powered coding agents are increasingly used to modify existing code repositories, for example, by adding features or fixing bugs.