Search: “models”

Perception or Reasoning? Diagnosing and Tackling Reinforcement Learning Bottlenecks in VLMs

arXiv:2610.21380v1 Announce Type: new Abstract: Reinforcement learning has brought strong gains to language model reasoning, but its improvements on visual tasks remain less consistent. One difficulty

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

SciPivot: Benchmarking Principal-Investigator Judgment at Pivotal Moments of Scientific AutoResearch Agents

DGX agent

arXiv:2610.21082v1 Announce Type: new Abstract: Large language model (LLM) agents can keep scientific experiments running for months with little human supervision, but reliable autonomous research als

model-releasesarxiv-cs-ai

16 Oct 2026

Seeing is Believing: Benchmarking and Mitigating the Interference of Language Priors on Visual Perception in MLLMs

arXiv:2610.21902v1 Announce Type: new Abstract: Language priors in MLLMs can override visual evidence, impairing visual perception. Existing benchmarks assume shared priors across models and rely sole

Applications

Self-Refining Vision Language Model for Robotic Failure Detection and Reasoning

arXiv:2602.12405v2 Announce Type: replace-cross Abstract: Reasoning about failures is crucial for building reliable and trustworthy robotic systems. Prior approaches either treat failure reasoning as

applicationsarxiv-cs-lg

TEM: Temporal State Tracking Memory for Large Language Model Agents

arXiv:2610.21900v1 Announce Type: new Abstract: An agent's memory must remain useful as information changes across conversations. A new fact may replace an earlier value without making that value irre

agentsarxiv-cs-cl

A VR Training System for Robot-Assisted Vascular Intervention with Dual-Mode Control and Model-Based Interaction Response

arXiv:2610.19413v1 Announce Type: new Abstract: Virtual reality training for robot-assisted vascular intervention requires accurate robotic control and effective feedback on guidewire--vessel interact

researcharxiv-cs-ro

Alignment Faking - the Train -> Deploy Asymmetry: Through a Game-Theoretic Lens with Bayesian-Stackelberg Equilibria

arXiv:2511.17937v2 Announce Type: replace Abstract: Alignment faking is a form of strategic deception in AI in which models selectively comply with training objectives when they infer that they are in

AutoMARS: Automatic and Scalable Multi-Agent Large Language Model Framework for Supply Chain Risk Assessment

arXiv:2610.17206v1 Announce Type: new Abstract: We propose AutoMARS (Automatic Multi-Agent Risk Assessment), an agentic framework for automatic and scalable comparative risk assessment in supply chain

agentsarxiv-cs-ai

AutoSec-RAN: Specification-Grounded LLM Fine-Tuning for Automated Security Analysis of O-RAN

arXiv:2610.15995v1 Announce Type: cross Abstract: This paper presents AutoSec-RAN, a specification-grounded large language model (LLM) framework for automated security triage of Open Radio Access Netw

Beyond Benchmark Accuracy: A Diagnostic Test for LLM Chemical Prediction

model-releasesarxiv-cs-cl

arXiv:2610.19906v1 Announce Type: new Abstract: LLMs have achieved strong performance on chemical prediction benchmarks. However, existing evaluation methods typically provide target entity identity i

Applications

Contact-UAN: Unsupervised Actuator Networks as a Residual World Model for Humanoid Control

arXiv:2610.18991v1 Announce Type: new Abstract: Humanoid policies trained in simulation can transfer qualitatively to hardware while failing to transfer the force interactions learned during training,

applicationsarxiv-cs-ro

FACT: A Multimodal Force-Action-Track Foundation Model for Human-to-Robot Dexterity

arXiv:2610.19155v1 Announce Type: new Abstract: Human demonstrations offer a scalable alternative to costly robot data collection for dexterous manipulation, but most human datasets lack force measure

agentsarxiv-cs-ro

Following the Flow the Law Requires: Training Voice Agents to Transfer to Unseen Regulated Procedures in Debt Collection

model-releasesarxiv-cs-cl

arXiv:2610.18881v1 Announce Type: new Abstract: Voice agents built on large language models (LLMs) now handle customer calls, but in regulated applications completing the task is not enough: the agent

GateSight: Recurrent Memory Anticipates Attention Memory for Query-Agnostic KV Eviction in Hybrid LLMs

arXiv:2610.14754v1 Announce Type: new Abstract: Hybrid language models interleave Gated DeltaNet (GDN) layers, whose recurrent memory has a fixed size, with full-attention layers, whose key-value (KV)

How Well Do LLMs Perform in Peer Review? Evidence from Finance and Accounting

arXiv:2610.18435v1 Announce Type: cross Abstract: Referees increasingly use large language models (LLMs), while finance and accounting journals disagree about whether to allow it. We ask which part of

I tested how ethnicity changes Krea 2 Turbo's output so you don't have to (77 ethnicities × 7 prompts, same seed)

model-releasesr-stablediffusion

Heads up: this is far from an academic analysis. It started as a quick check out of my own curiosity and grew a bit from there. The research was mostly guided by AI (Claude), which suggested the compa

Local Ai

ibm-granite/granite-switch-4.1 30B/8B

Granite Switch 4.1 30B 📝 Read the launch blog: Granite Switch 4.1: Chat, Decisions, and Speech from One Endpoint Model Summary: Granite Switch 4.1 30B is a modular LLM that composes a base model, mult

local-air-localllama

Language Steering for Multilingual In-Context Learning

model-releasesarxiv-cs-cl

arXiv:2602.02326v3 Announce Type: replace Abstract: If multilingual language model representations contain separable language-associated structure, then shifting between languages may require only sim

Hardware

Learning in Orbit: Onboard Training and Closed-Loop Attitude Control with a Thermal Segmentation Model on a Spacecraft

arXiv:2610.19122v1 Announce Type: new Abstract: Deep space missions increasingly require spacecraft capable of autonomously operating in environments with communication delays and bandwidth limitation

hardwarearxiv-cs-ro

Physics-Guided Multi-Fidelity Surrogate Modeling for Natural Supercavity Geometry of an Axisymmetric Conical Cavitator

arXiv:2610.18886v1 Announce Type: cross Abstract: Natural supercavitation behind conical cavitators generates a vapor-filled envelope that, when sustained over the full body of a high-speed underwater

researcharxiv-cs-lg

Reliable Text-to-SQL in Resource-Constrained Settings with Small LLMs via Iterative Retry Workflows

arXiv:2610.17305v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently improved Text-to-SQL generation, but their computational cost can hinder deployment in resource-constrained s

Tutorials

ROI-Reasoning: Rational Optimization for Inference via Pre-Computation Meta-Cognition

arXiv:2601.03822v2 Announce Type: replace Abstract: Large language models (LLMs) can achieve strong reasoning performance with sufficient computation, but they do not inherently know how much computat

tutorialsarxiv-cs-ai

Scaling Multilingual Mixture-of-Experts: How Language Coverage Changes Capacity and Compute Allocation

arXiv:2610.20247v1 Announce Type: new Abstract: Multilingual models share capacity across languages, so adding languages can hurt performance on existing ones. Mixture-of-experts models expand this ca

researcharxiv-cs-cl

The Sharp Directions Are Against You: Curvature Analysis of Activation Steering

arXiv:2610.16084v1 Announce Type: new Abstract: Activation steering adds a vector to a language model's internal representations at inference time. It is a lightweight alternative to fine-tuning for b

Towards Efficient Simultaneous Inverse Text Normalization with Pretrained Text-to-Text Language Model and Read-Tag-Write Policy

arXiv:2610.19492v1 Announce Type: new Abstract: Streaming Inverse Text Normalization (ITN) is vital for converting spoken-form outputs from streaming Automatic Speech Recognition into formatted writte

safetyarxiv-cs-cl

Transparent Information Flow Modeling for Role-Aware AI Act Assessment

arXiv:2610.16916v1 Announce Type: new Abstract: The European Union's Artificial Intelligence Act introduces a structured framework for governing high-risk AI systems, emphasizing transparency, risk ma

safetyarxiv-cs-ai

Using Evidence-Centered Design to Guide Prompt Engineering in Measurement: An Illustration with Automated Essay Scoring

arXiv:2610.15231v1 Announce Type: new Abstract: Generative artificial intelligence (GenAI) models, particularly large language models (LLMs), are increasingly used in educational settings for tasks su

safetyarxiv-cs-ai

v0.40.5

model-releasesollama-releases

NVIDIA Nemotron 3.5 Super NVIDIA Nemotron 3.5 Super is a vision-language model for coding, reasoning, tool use, and document understanding. It pairs a 120B-parameter hybrid Mamba-2/Transformer mixture

When Skills Remain But Access Fails: Factorized Skill Memory for Continual Skill Internalization

arXiv:2610.15492v1 Announce Type: new Abstract: Skill internalization aims to convert externally specified procedural skills into persistent model capabilities, allowing language-model agents to execu

Why Do VLMs Fail at Remote Physiological Measurement? Rethinking with Physiological Grounding and Numerical Alignment

arXiv:2610.19052v1 Announce Type: new Abstract: Video-based remote physiological measurement (RPM) has broad applications, while Vision-Language Models (VLMs) provide a promising opportunity to enable

APT: Feedback-Driven Agentic Post-Training for Text-to-Image Generation

arXiv:2610.18097v1 Announce Type: new Abstract: Post-training is crucial for improving text-to-image models, yet existing pipelines typically rely on manually curated training data and fixed training

As I’ve been saying, LangChain is going to be the leader in composable AI because their tech is perfect for stitching together all of these …

As I’ve been saying, LangChain is going to be the leader in composable AI because their tech is perfect for stitching together all of these smaller specialized models. And now we have another category

agentsharrison-chase--x

Deep learning from a control vantage point

arXiv:2610.14385v1 Announce Type: cross Abstract: This article offers an overview of recent developments in deep learning from a control vantage point. It reviews several classes of models including f

researcharxiv-cs-lg

Diversity You Can Actually Measure: A Fast, Model-Free Diversity Metric for Robotics Datasets

arXiv:2603.11634v2 Announce Type: replace Abstract: Robotics datasets for imitation learning typically consist of long-horizon trajectories of different lengths over states, actions, and high-dimensio

safetyarxiv-cs-ro

Efficient Resource-Shiftable RL Post-training with Generative Rewards

arXiv:2610.16866v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training with generative reward models (GenRM) has become a central recipe for improving large language models (LLMs),

EmoGenie: Benchmarking and Evaluating Expressed and Evoked Emotion in T2I Generation with MLLMs

arXiv:2610.18455v1 Announce Type: new Abstract: Rapid advances in artificial intelligence-generated content (AIGC) have significantly promoted using text-to-image (T2I) models to generate images with

Local Ai

Failure Recovery via Belief Updates and World Modeling for Long-Horizon Agents

arXiv:2610.18082v1 Announce Type: new Abstract: Long-horizon agents often struggle to recover from failures whose causes lie several steps earlier, beyond what local reflection or backtracking can res

local-aiarxiv-cs-lg

FETALFusion: Resolution-Aware State-Space Modeling for Multi-Domain Fetal Head Segmentation

arXiv:2610.17951v1 Announce Type: new Abstract: Head circumference (HC) measured from 2D ultrasound is a routine marker of fetal growth, and automating it needs segmentations whose boundaries hold up

researcharxiv-cs-cv

GA-SVD: Generation-aware Singular Value Decomposition for LLM Compression

arXiv:2610.15398v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong generalization across a broad range of reasoning and generation tasks, but their large parameter counts

Integrating AIRL-Based Reward Estimation into a Control Method Using Fuzzy Inference and Policy Gradient

arXiv:2610.14723v1 Announce Type: new Abstract: A method integrating policy gradient with fuzzy inference has been proposed. This method, hereafter referred to as the base model, has high flexibility

safetyarxiv-cs-lg

LoOPSD: On-Policy Self-Distillation with Looped Teachers

arXiv:2610.18162v1 Announce Type: new Abstract: On-policy self-distillation improves a model using guidance from the model itself, but it still requires a teacher that provides more useful predictions

safetyarxiv-cs-lg

LoRAtorio: An intrinsic approach to LoRA Skill Composition

arXiv:2508.11624v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has become a widely adopted technique in text-to-image diffusion models, enabling the personalisation of visual concepts

researcharxiv-cs-cv

ManipShield: A Unified Framework for Image Manipulation Detection, Localization and Explanation

arXiv:2511.14259v4 Announce Type: replace Abstract: With the rapid advancement of generative models, powerful image editing methods now enable diverse and highly realistic image manipulations that far

Model-Based Trailer-Sway Suppression for Autonomous Passenger Vehicles

arXiv:2610.15747v1 Announce Type: new Abstract: Trailer sway is a persistent contributor to severe crashes among light passenger vehicles towing trailers, yet it remains largely unaddressed by the aut

agentsarxiv-cs-ro

On the Monitorability of Natural Language Autoencoders: Identification vs Discrimination

arXiv:2610.18727v1 Announce Type: new Abstract: Natural Language Autoencoders (NLAs) are proposed as oversight tools for language models: an Activation Verbaliser (AV) writes an English explanation of

PhySimCode: A Benchmark and Evaluation Method for Physics Video to Code Generation

arXiv:2610.15722v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are good at video understanding and code generation, but it remains unclear whether they can recover the physic

SEAR: Self-Evolving Agentic Robotics

model-releasesarxiv-cs-ro

arXiv:2610.18792v1 Announce Type: new Abstract: Frontier language-model agents can now improve robots on their own: they write control code, test it, and keep what works as skills and memories for the

SLEM: Spectrum-Aware Latent Expert Merging

arXiv:2610.16484v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models scale model capacity efficiently by activating only a small subset of experts for each input, while still requiring all