Search: “reasoning”

Nemotron 3 Nano Omni is now in LM Studio! A new 30B multi-modal MoE from @nvidia Supports Image input, reasoning, and tool use Requires ~25GB to run locally 🔥🚀 https://lmstudio.ai/models/nemotron-3-om

arXiv:2512.15930v2 Announce Type: replace-cross Abstract: Intrinsically disordered proteins (IDPs) represent crucial therapeutic targets due to their significant role in disease -- approximately 80% o

arXiv:2604.23747v1 Announce Type: cross Abstract: Recent mixed-policy optimization methods for LLM reasoning that interleave or blend supervised and reinforcement learning signals report improvements

arXiv:2511.08577v2 Announce Type: replace-cross Abstract: Improving reasoning abilities of Large Language Models (LLMs), especially under parameter constraints, is crucial for real-world applications.

arXiv:2604.22294v1 Announce Type: cross Abstract: Real-world document question answering is challenging. Analysts must synthesize evidence across multiple documents and different parts of each documen

DeepSeek V4-Pro is live on Fireworks: → Frontier-class coding and reasoning, open-weights → 1M context standard, MIT licensed → 1.74 / 3.48 per 1M tok Get started now → https://app.fireworks.ai/models

arXiv:2604.21935v1 Announce Type: new Abstract: Although language models demonstrate remarkable proficiency on mathematical benchmarks, it remains unclear whether this reflects true mathematical reaso

arXiv:2604.22136v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly issue API calls that mutate real systems, yet many current architectures pass stochastic model outputs

arXiv:2604.22156v1 Announce Type: cross Abstract: Purpose: Accurate assessment of the Critical View of Safety (CVS) during laparoscopic cholecystectomy is essential to prevent bile duct injury, a comp

arXiv:2506.05038v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in various reasoning-intensive tasks. However, these models exhibit unexpecte

arXiv:2604.21334v1 Announce Type: new Abstract: Do large language models (LLMs) exhibit systematic ideological bias when reasoning about economic causal effects? As LLMs are increasingly used in polic

Introducing DeepSeek V4 Pro, a long-context model with hybrid attention, three reasoning modes, and SOTA coding performance. AI natives can now use DeepSeek V4 Pro on Together AI and benefit from reli

arXiv:2604.21249v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) enable high-level semantic reasoning for end-to-end autonomous driving, particularly in unstructured environments, e

arXiv:2604.20917v1 Announce Type: cross Abstract: Large language models (LLMs) have shown remarkable capabilities across diverse coding tasks. However, their adoption requires a true understanding of

Anthropic: Anthropic says it has fixed three causes of recent Claude Code quality issues: reduced default reasoning, a caching bug, and a system prompt to reduce verbosity — We traced recent reports o

arXiv:2604.20263v1 Announce Type: cross Abstract: Virtual cell modeling predicts molecular state changes under genetic perturbations in silico, which is essential for biological mechanism studies. How

This Reddit discussion post addresses a beginner's question about choosing between 3B and 7B parameter models for fine-tuning on multi-task reasoning problems. The post likely contains advice from exp

arXiv:2604.20560v1 Announce Type: new Abstract: Automatically filling Case Report Forms (CRFs) from clinical notes is challenging due to noisy language, strict output contracts, and the high cost of f

arXiv:2604.20283v1 Announce Type: new Abstract: Multimodal Entity Linking (MEL) is a fundamental task in data management that maps ambiguous mentions with diverse modalities to the multimodal entities

Madison Mills / Axios: OpenAI says GPT-5.5's improvements are strongest in agentic coding, computer use, and early scientific research, which require reasoning across longer contexts — OpenAI on Thurs

arXiv:2604.20665v1 Announce Type: cross Abstract: The rapid proliferation of Vision-Language Models (VLMs) is widely celebrated as the dawn of unified multimodal knowledge discovery but its foundation

tldr: claude code changed some harness settings which degraded perf. these small harness tweaks can matter a lot! 1. default reasoning high -> medium 2. bug that accidentally evicted thinking blocks o

arXiv:2604.20043v1 Announce Type: cross Abstract: Explainability for Large Language Model (LLM) agents is especially challenging in interactive, partially observable settings, where decisions depend o

arXiv:2604.18964v1 Announce Type: new Abstract: This paper introduces DW-Bench, a new benchmark that evaluates large language models (LLMs) on graph-topology reasoning over data warehouse schemas, exp

arXiv:2604.18897v1 Announce Type: new Abstract: We present a systematic empirical study of prompt engineering for formal mathematical reasoning in the context of the SAIR Equational Theories Stage 1 c

ml-intern by @huggingface is wild 🔥 You drop a high-level prompt (“build the best scientific reasoning model” or “crush healthcare benchmarks”) and this open-source agent does the entire post-training

arXiv:2604.00555v2 Announce Type: replace Abstract: Enterprise adoption of Large Language Models (LLMs) is constrained by hallucination, domain drift, and the inability to enforce regulatory complianc

Qwen3.6 27B is now in LM Studio! Vision, reasoning, and agentic tool calling - running locally on your computer. Surpasses previous Qwen models many times its size 🚀👾🔥 https://lmstudio.ai/models/qwen/

arXiv:2604.17821v2 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have empowered autonomous web agents to execute natural language instructions directly on real-w

arXiv:2603.05569v2 Announce Type: replace-cross Abstract: Extracting insights from Electronic Health Record (EHR) databases often requires SQL expertise, creating a barrier for clinical decision-makin

arXiv:2604.16930v1 Announce Type: new Abstract: Visual Question Answering (VQA) requires models to identify the correct answer options based on both visual and textual evidence. Recent Mixture-of-Expe

arXiv:2604.16456v1 Announce Type: new Abstract: Real-time voice assistants must revise task state when users interrupt mid-response, but existing spoken-dialog benchmarks largely evaluate turn-based i

arXiv:2410.04509v3 Announce Type: replace Abstract: As the field of Multimodal Large Language Models (MLLMs) continues to evolve, their potential to revolutionize artificial intelligence is particular

arXiv:2604.04825v2 Announce Type: replace Abstract: Large language models achieve strong performance on many language tasks, yet it remains unclear whether they integrate world knowledge with syntacti

arXiv:2604.16909v1 Announce Type: new Abstract: As large language models (LLMs) evolve from conversational assistants into agents capable of handling complex tasks, they are increasingly deployed in h

arXiv:2601.02970v2 Announce Type: replace Abstract: Self-Consistency improves reasoning reliability through multi-sample aggregation, but incurs substantial inference cost. Adaptive self-consistency m

arXiv:2505.13353v4 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed for understanding large codebases, but whether they understand operational semantics of long

arXiv:2604.14334v2 Announce Type: replace-cross Abstract: Gradient saliency from deep sequence models surfaces candidate biomarkers efficiently, but the resulting gene lists can be contaminated by tis

Our researchers are heading to ICLR with new work: model efficiency, long-context reasoning, next-gen attention and decoding, and more. Check out what we've been building 👇🏼 #TogetherResearch #AINativ

arXiv:2604.14853v1 Announce Type: new Abstract: Test-time compute scaling, the practice of spending extra computation during inference via repeated sampling, search, or extended reasoning, has become

arXiv:2603.01410v2 Announce Type: replace Abstract: Knowledge graphs provide structured and reliable information for many real-world applications, motivating increasing interest in combining large lan

arXiv:2604.14164v1 Announce Type: new Abstract: A widely adopted strategy for model enhancement is to use synthetic data generated by a stronger model for supervised fine-tuning (SFT). However, for em

This Google Research work presents guidelines for synthetic data mechanism design and provides insights into generating and evaluating synthetic data at scale. The research introduces a reasoning-driv

@GaryMarcus Essentially your prediction that LLMs to scale wouldn’t solve key fundamental problems, reasoning, factual reliability, compositionality, grounded understanding etc are now elephantine chi

In this post, you'll learn why probabilistic AI validation falls short in regulated industries and how Automated Reasoning checks use formal verification to deliver mathematically proven results. You'

GPT-Rosalind is a frontier reasoning model developed by OpenAI, specifically designed to support research applications in biology, drug discovery, and translational medicine. The model was introduced