Search: “reasoning”

Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation

arXiv:2604.08627v1 Announce Type: cross Abstract: Pretrained models have become standard in both vision and language, yet they typically do not provide reliable measures of confidence. Existing uncert

applicationsarxiv-cs-ai

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

FP8-RL: A Practical and Stable Low-Precision Stack for LLM Reinforcement Learning

DGX agent

arXiv:2601.18150v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is increasingly bottlenecked by rollout (generation), where long output sequence

safetyarxiv-cs-cl

13 Apr 2026

Investigating Multimodal Large Language Models to Support Usability Evaluation

arXiv:2508.16165v2 Announce Type: replace-cross Abstract: Usability evaluation is an essential method to support the design of effective and intuitive user interfaces (UIs). However, it commonly relie

applicationsarxiv-cs-ai

p1: Better Prompt Optimization with Fewer Prompts

arXiv:2604.08801v1 Announce Type: cross Abstract: Prompt optimization improves language models without updating their weights by searching for a better system prompt, but its effectiveness varies wide

researcharxiv-cs-cl

PerMix-RLVR: Preserving Persona Expressivity under Verifiable-Reward Alignment

arXiv:2604.08986v1 Announce Type: cross Abstract: Persona prompting has been widely adopted to steer large language models (LLMs) behavior and improve their instruction performance by assigning specif

safetyarxiv-cs-ai

Region-Constrained Group Relative Policy Optimization for Flow-Based Image Editing

arXiv:2604.09386v1 Announce Type: new Abstract: Instruction-guided image editing requires balancing target modification with non-target preservation. Recently, flow-based models have emerged as a stro

ScheMatiQ: From Research Question to Structured Data through Interactive Schema Discovery

arXiv:2604.09237v1 Announce Type: new Abstract: Many disciplines pose natural-language research questions over large document collections whose answers typically require structured evidence, tradition

applicationsarxiv-cs-cl

SynDocDis: A Metadata-Driven Framework for Generating Synthetic Physician Discussions Using Large Language Models

arXiv:2604.08555v1 Announce Type: new Abstract: Physician-physician discussions of patient cases represent a rich source of clinical knowledge and reasoning that could feed AI agents to enrich and eve

applicationsarxiv-cs-cl

Towards Knowledgeable Deep Research: Framework and Benchmark

arXiv:2604.07720v2 Announce Type: replace Abstract: Deep Research (DR) requires LLM agents to autonomously perform multi-step information seeking, processing, and reasoning to generate comprehensive r

After seeing that Claude Mythos marketing turned out to be, as expected, a scam, I wanted to make a master list of tricks being used to mark…

model-releasesyann-lecun--x

After seeing that Claude Mythos marketing turned out to be, as expected, a scam, I wanted to make a master list of tricks being used to market LLMs. The master list includes statements directly from l

12 Apr 2026

model page: https://ollama.com/library/minimax-m2.7

MiniMax-M1 is a large-scale open-weight reasoning model developed by MiniMax, featuring a hybrid Mixture-of-Experts (MoE) architecture with 456 billion total parameters (activating 45.9 billion per to

local-aiollama--x

12 Apr 2026

Concepts

All Companies

Auto-generated index of all companies mentioned across the wiki.

conceptscompaniesindex

11 Apr 2026

b8744

local-aillama-cpp-releases

llama.cpp release **b8744**, published on April 10, 2026, is a build of the ggml-org/llama.cpp C/C++ LLM inference engine. Its primary change enables the reasoning budget sampler for Gemma 4 by add...

Blind Refusal: Language Models Refuse to Help Users Evade Unjust, Absurd, and Illegitimate Rules

arXiv:2604.06233v1 Announce Type: new Abstract: Safety-trained language models routinely refuse requests for help circumventing rules. But not all rules deserve compliance. When users ask for help eva

Chunks as Arms: Multi-Armed Bandit-Guided Sampling for Long-Context LLM Preference Optimization

model-releasesarxiv-cs-cl

arXiv:2508.13993v2 Announce Type: replace Abstract: Long-context modeling is critical for a wide range of real-world tasks, including long-context question answering, summarization, and complex reason

Countering the Over-Reliance Trap: Mitigating Object Hallucination for LVLMs via a Self-Validation Framework

arXiv:2601.22451v2 Announce Type: replace-cross Abstract: Despite progress in Large Vision Language Models (LVLMs), object hallucination remains a critical issue in image captioning task, where models

EVGeoQA: Benchmarking LLMs on Dynamic, Multi-Objective Geo-Spatial Exploration

arXiv:2604.07070v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable reasoning capabilities, their potential for purpose-driven exploration in dynamic geo-spatial

HY-Embodied-0.5: Embodied Foundation Models for Real-World Agents

model-releasesarxiv-cs-cv

arXiv:2604.07430v1 Announce Type: new Abstract: We introduce HY-Embodied-0.5, a family of foundation models specifically designed for real-world embodied agents. To bridge the gap between general Visi

Large Language Model Post-Training: A Unified View of Off-Policy and On-Policy Learning

arXiv:2604.07941v1 Announce Type: new Abstract: Post-training has become central to turning pretrained large language models (LLMs) into aligned and deployable systems. Recent progress spans supervise

safetyarxiv-cs-cl

Making MLLMs Blind: Adversarial Smuggling Attacks in MLLM Content Moderation

model-releasesarxiv-cs-cv

arXiv:2604.06950v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) are increasingly being deployed as automated content moderators. Within this landscape, we uncover a critic

Agents

MedRoute: RL-Based Dynamic Specialist Routing in Multi-Agent Medical Diagnosis

arXiv:2604.06180v1 Announce Type: cross Abstract: Medical diagnosis using Large Multimodal Models (LMMs) has gained increasing attention due to capability of these models in providing precise diagnose

agentsarxiv-cs-lg

MSCT: Differential Cross-Modal Attention for Deepfake Detection

arXiv:2604.07741v1 Announce Type: new Abstract: Audio-visual deepfake detection typically employs a complementary multi-modal model to check the forgery traces in the video. These methods primarily ex

OpenSpatial: A Principled Data Engine for Empowering Spatial Intelligence

arXiv:2604.07296v2 Announce Type: replace Abstract: Spatial understanding is a fundamental cornerstone of human-level intelligence. Nonetheless, current research predominantly focuses on domain-specif

applicationsarxiv-cs-cl

Q-Zoom: Query-Aware Adaptive Perception for Efficient Multimodal Large Language Models

arXiv:2604.06912v1 Announce Type: cross Abstract: MLLMs require high-resolution visual inputs for fine-grained tasks like document understanding and dense scene perception. However, current global res

local-aiarxiv-cs-ai

RoboAgent: Chaining Basic Capabilities for Embodied Task Planning

arXiv:2604.07774v1 Announce Type: cross Abstract: This paper focuses on embodied task planning, where an agent acquires visual observations from the environment and executes atomic actions to accompli

SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs

arXiv:2604.07737v1 Announce Type: new Abstract: While transformer-based Large Language Models (LLMs) theoretically support massive context windows, they suffer from severe performance degradation when

local-aiarxiv-cs-cl

Tutorials

Steering the Verifiability of Multimodal AI Hallucinations

arXiv:2604.06714v1 Announce Type: new Abstract: AI applications driven by multimodal large language models (MLLMs) are prone to hallucinations and pose considerable risks to human users. Crucially, su

tutorialsarxiv-cs-ai

SVGFusion: A VAE-Diffusion Transformer for Vector Graphic Generation

arXiv:2412.10437v3 Announce Type: replace Abstract: Generating high-quality Scalable Vector Graphics (SVGs) from text remains a significant challenge. Existing LLM-based models that generate SVG code

researcharxiv-cs-cv

VLMShield: Efficient and Robust Defense of Vision-Language Models against Malicious Prompts

arXiv:2604.06502v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face significant safety vulnerabilities from malicious prompt attacks due to weakened alignment during visual integration.

safetyarxiv-cs-lg

When to Call an Apple Red: Humans Follow Introspective Rules, VLMs Don't

arXiv:2604.06422v1 Announce Type: cross Abstract: Understanding when Vision-Language Models (VLMs) will behave unexpectedly, whether models can reliably predict their own behavior, and if models adher

WRAP++: Web discoveRy Amplified Pretraining

arXiv:2604.06829v2 Announce Type: cross Abstract: Synthetic data rephrasing has emerged as a powerful technique for enhancing knowledge acquisition during large language model (LLM) pretraining. Howev

FlowInOne - A new Multimodal image model . Released on Huggingface

model-releasesr-stablediffusion

FlowInOne is a vision-centric multimodal image generation framework that reformulates multimodal generation as a purely visual flow, converting all inputs into visual prompts and enabling a clean i...

9 Apr 2026

Tools

Stop trusting LLMs just because they're useful. 🛑 Our Head of DevRel @RoieSchwabco breaks down the two essential parts of a reliable AI sta…

Stop trusting LLMs just because they're useful. 🛑 Our Head of DevRel @RoieSchwabco breaks down the two essential parts of a reliable AI stack: ⚙️ Reasoning: What the LLM does (logic/synthesis/formatti

toolspinecone--x

9 Apr 2026

Visually rich documents are especially challenging for agents. Tables, charts, and images often break traditional document pipelines, making…

model-releasesjerry-liu--x

Visually rich documents are especially challenging for agents. Tables, charts, and images often break traditional document pipelines, making complex reasoning difficult📄 So we teamed up with @lancedb

7 Apr 2026

Nine models, five coding tasks, one 16GB GPU

model-releasesr-localllama

I ran five coding tasks against nine models on one RX 9060 XT (16 GB). Each run gets a single spec file in an empty directory and has to produce solution.py and test_solution.py, run its own tests, an

18 Oct 2026

b11709

model-releasesllama-cpp-releases

model : add Kolibri-1 (Aleph-Alpha) support (#30673) model : add Kolibri-1 (Aleph-Alpha) support Kolibri-1 is a bilingual German/English MoE reasoning model with 78B parameters and 3.46B active per to

17 Oct 2026

llama.cpp has come a long way

model-releasesr-localllama

Hey everyone, English is not my native language (Dutch), but I write in my own words without assistance. So please let me know if any sentence flows weird, etc. A mate of mine told me how amazing loca

17 Oct 2026

AdaLoop: Thinking with the Vision Encoder

arXiv:2610.21323v1 Announce Type: new Abstract: Most vision-language models (VLMs) treat the vision encoder as a static feature extractor: it encodes an image once, independently of the question, and

researcharxiv-cs-cv

ARC-SORT: Adaptive, Robust, Compensated Multi-Object Tracking with Interacting Multiple Models

model-releasesarxiv-cs-cv

arXiv:2610.22306v1 Announce Type: new Abstract: Multi-object tracking in sports broadcasts is hard for two reasons: athletes move fast and change direction abruptly, and the camera pans and zooms at t

AutoOnboarder: Autonomously Onboarding LLM Agents

arXiv:2610.21218v1 Announce Type: new Abstract: Agentic large language models have been documented to lose reasoning capability when placed inside a harness, the software that mediates their observati

Agents

CARA: Causally Guided Retrieval Agent for Question Answering

arXiv:2610.22017v1 Announce Type: new Abstract: Retrieval-augmented generation over text-rich knowledge graphs requires identifying evidence that contributes to answering a question, rather than merel

agentsarxiv-cs-ai

Do Agents Need a New Kind of Paper? SPRA: Structured Paper Representation for Agents

arXiv:2610.21424v1 Announce Type: new Abstract: Scientific agents must connect research problems, methods, and findings dispersed through narrative articles. We introduce SPRA (Structured Paper Repres

Do As I Do, Not As I Say: On-Policy Distillation Inherits the Teacher in Vision-Language Models

arXiv:2610.20989v1 Announce Type: cross Abstract: Improving the reasoning capabilities of vision-language models (VLMs) often relies on post-training with supervision from stronger models. Two common

EliteReplay: Preserving Diverse Solutions in RL Post-Training via Quality-Diversity Search

arXiv:2610.22290v1 Announce Type: new Abstract: Reinforcement learning has become a common post-training technique to improve the accuracy of LLMs on verifiable tasks. However, such training can narro

HTN-Orchestrate: A Hierarchical Task Network Framework for Multi-Agent Orchestration

arXiv:2610.22195v1 Announce Type: new Abstract: Orchestrating multiple agents on a complex task requires reconciling local subtask execution with global task planning. Dynamic dispatch approaches prov

Agents

Knowledge graphs fuel AI innovation for financial services at Raymond James Financial

Knowledge graphs are becoming a critical context and reasoning layer for agentic AI, helping enterprises connect data and ground agents in key areas of business expertise. For diversified financial se

agentssiliconangle

Orchestrating LLM Agents for Scientific Research: A Pilot Study of Multiple Choice Question (MCQ) Generation and Evaluation

arXiv:2602.18891v2 Announce Type: replace-cross Abstract: Advances in large language models (LLMs) are rapidly transforming scientific work, yet empirical evidence on how these systems reshape researc

safetyarxiv-cs-ai

RecSoup: Efficient Model Merging Approach for Controllable Multi-Objective Recommendation

arXiv:2610.21220v1 Announce Type: cross Abstract: Recommender systems often need to balance multiple conflicting objectives. Controllable Multi-Objective Recommendation (CMOR) enables dynamic adjustme