Search: “framework”

Interpreting and Steering LLM Agents for Social Simulations

arXiv:2609.16436v1 Announce Type: cross Abstract: Simulations based on large language models (LLMs) have proven to be powerful for understanding human behavior, making them valuable additions to the s

Latent Undertow: How Ordinary Typos Break Probes

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2609.15994v1 Announce Type: new Abstract: LLMs handle ordinary typing variation fluently: a typo or missing punctuation leaves both user intent and the model's response substantively unchanged.

model-releasesarxiv-cs-cl

16 Sept 2026

little m: An AI Agent for Industrial Process Optimization

arXiv:2609.16680v1 Announce Type: new Abstract: Manufacturing consumes one third of global energy and still has significant room for improvement in terms of energy efficiency. Optimal process control

Tutorials

LM-PCVMNet: Pediatric Cervical Vertebral Maturation Analysis with Deep Fusion of Landmarks and Metadata

arXiv:2609.16033v1 Announce Type: cross Abstract: Cervical vertebral maturation (CVM) assessment plays a pivotal role in orthodontic diagnosis and determining the optimal timing of treatment, especial

tutorialsarxiv-cs-cv

Agents

Models as Governed Interfaces for AI-Native MBSE: Read-Side Adequacy and Write-Side Admissibility

arXiv:2609.16252v1 Announce Type: cross Abstract: Machine-readable models such as SysML v2 are now programmatically accessible, and a growing body of work treats that access as the enabling condition

agentsarxiv-cs-ai

Applications

Multi-Label Proportion Learning for Sea-Ice Type Prediction

arXiv:2609.16347v1 Announce Type: new Abstract: Sea-ice type prediction is important for climate monitoring, maritime navigation, and decision-making in polar regions. The main source of label data fo

applicationsarxiv-cs-lg

MUMINS: Metadata-conditioned Uncertainty-aware Medical Image Next-state Synthesis

arXiv:2609.17169v1 Announce Type: cross Abstract: Forecasting anatomical changes such as tumor growth and neurodegeneration is a challenging generative vision task. Morphological evolution is subtle r

My name is Chris Painter, and I'm the President of METR (Model Evaluation and Threat Research). I know we've made a lot of new friends on th…

My name is Chris Painter, and I'm the President of METR (Model Evaluation and Threat Research). I know we've made a lot of new friends on the internet the last couple of days, so I thought I'd take th

safetyyohei-nakajima--x

NeuroTS-Net: Multi-Class Semantic Segmentation of Pediatric Brain Tumors in Multi-Modal MRI

arXiv:2609.16873v1 Announce Type: new Abstract: Pediatric brain tumors are a leading cause of cancer-related mortality in children, and their small, rare, and often low-contrast subregions make accura

researcharxiv-cs-cv

Never Stop Thinking: Continuous-Time Language Agents

arXiv:2609.17416v1 Announce Type: new Abstract: Voice agents built on LLMs follow a rigid listen-think-speak loop that inserts seconds of dead air before every reply. We show that continuous-time cogn

OmniHarness: Harnessing Generalizable Visual Generation via Symbolic Policy Learning

arXiv:2609.16057v1 Announce Type: cross Abstract: Unified multimodal large language models (MLLMs) and multi-agent systems have advanced visual generation. However, three limitations remain. (1) Exist

Optimizing agent system prompts with Amazon Bedrock AgentCore

model-releasesaws-ml-blog

AgentCore optimization turns production traces into proposed configuration changes, then validates them before promotion. This technical companion to the launch post explains how the system prompt opt

ORDER: Task-Conditioned Routing for Retrieval-Augmented Generation

arXiv:2609.17012v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) pipelines typically rely on a fixed indexing and retrieval configuration determined at preprocessing time. This one

Agents

PaperDoctor: Evidence-Grounded and Actionable Feedback for Scientific Papers in Progress

arXiv:2609.16995v1 Announce Type: new Abstract: Autoresearch agents are reshaping the research ecosystem, but they can also let flawed claims enter the literature at scale. Human advisors catch such i

agentsarxiv-cs-cl

Local Ai

PiPS: Post-Hoc Prototypical Explanations for Interpretable Semantic Segmentation

arXiv:2609.16909v1 Announce Type: new Abstract: With the increasing deployment of deep neural networks in critical systems, such as medical diagnostics and autonomous vehicles, ensuring their interpre

local-aiarxiv-cs-cv

Quantifying Organizational Environmental Action from Web Data and Large Language Models

arXiv:2609.16627v1 Announce Type: new Abstract: Quantifying organizational environmental action from publicly available web content remains a challenging environmental data science problem because rel

researcharxiv-cs-cl

Reduced-Space Multi-Fidelity Bayesian Optimization of Process Simulation Models

arXiv:2609.17440v1 Announce Type: new Abstract: Optimizing industrial process flowsheets is often computationally prohibitive due to the high cost of rigorous simulations and the curse of dimensionali

researcharxiv-cs-lg

Agents

Rene has a really neat multiplayer agentic experience. I run several agents at once. So I lose track of important conversations throughout t…

Rene has a really neat multiplayer agentic experience. I run several agents at once. So I lose track of important conversations throughout the day. Rene pulls conversations from my inbox and manages t

agentsdair-ai--x

Local Ai

RepoAtlas: Guiding Coding Agents via Evolving Multimodal Repository Views

arXiv:2609.16936v1 Announce Type: cross Abstract: Large language model (LLM)-powered coding agents have made rapid progress in automating software engineering tasks, yet repository-level issue resolut

local-aiarxiv-cs-ai

Robust Fault Detection in Mechanical Multimodal Time Series via Self-Supervised Cross-Modal Reconstruction

arXiv:2609.16314v1 Announce Type: new Abstract: Fault detection is essential in industrial systems, enabling early identification of abnormal behaviour and improving safety, reliability, and operation

safetyarxiv-cs-lg

Same Answer, Different Representations: Hidden instability in VLMs

arXiv:2602.06652v2 Announce Type: replace Abstract: The robustness of Vision Language Models (VLMs) is commonly assessed through output-level invariance, implicitly assuming that stable predictions re

ScienceBuddy: Recursive-in-Recursive Self-Improvement for Interactive Scientific Agents

arXiv:2609.17523v1 Announce Type: new Abstract: We introduce and release ScienceBuddy, an interactive scientific research workspace that brings continually improving scientific agents into researchers

SciNLP: A Domain-Specific Benchmark for Full-Text Scientific Entity and Relation Extraction in NLP

arXiv:2509.07801v5 Announce Type: replace Abstract: Structured information extraction from scientific literature is crucial for capturing core concepts and emerging trends in specialized fields. While

Tutorials

Seeing What Matters: Visual Cue Guided Video Planning for Generalizable Robot Navigation

arXiv:2609.16737v1 Announce Type: cross Abstract: Generative video models can serve as a promising backbone for robot navigation by predicting future observations as video plans. Recent approaches oft

tutorialsarxiv-cs-ai

Self-reported archetypes and behavioral failures in Large Language Models

arXiv:2609.15998v1 Announce Type: new Abstract: Every large language model (LLM) has behavioral traits and moral preferences that comprise its character. Whether by design or as an emergent property o

Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission

arXiv:2609.16279v1 Announce Type: cross Abstract: Emerging physical AI systems require low-latency, task-oriented video communication over unreliable channels. We propose a semantic-aware multi-level

researcharxiv-cs-lg

Shielded Analysis: Certification and Characterization of Defensibility in Systems under Adversarial Interaction

arXiv:2606.13621v2 Announce Type: replace Abstract: Formal safety analysis determines whether a system admits a safe defense; adaptive evaluation characterizes the operating quality sustained under ad

Stable by Construction: Variational Latent Markov Operators for Long-Horizon PDE Prediction

arXiv:2609.16621v1 Announce Type: new Abstract: Neural PDE solvers provide efficient surrogates for time-dependent physical systems, but autoregressive prediction over long horizons remains challengin

safetyarxiv-cs-lg

State of Thought Enables Endogenous Reasoning

arXiv:2609.16055v1 Announce Type: cross Abstract: Test-time compute has emerged as a major approach to improving the capabilities of Large Language Models (LLMs). However, existing test-time reasoning

The Immutable Past: Formalizing State Mutability and Conflict Resolution in Mutable RAG

arXiv:2609.16073v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) serves as the primary memory architecture for long-horizon autonomous agents. However, treating shared memory as

Applications

The Role of Implicit and Explicit Demographic Signals in Large Language Model-based Student Assessment

arXiv:2609.16993v1 Announce Type: cross Abstract: Large Language Models are now common in student assessment, but we know little about how student demographics affect their use. Sometimes, considering

applicationsarxiv-cs-ai

The Verifier is the Curriculum: Precision Sets the Return on Search in Code Self-Distillation

arXiv:2607.09709v2 Announce Type: replace Abstract: Post-training a code generator against a learned judge can optimize proxy features that raise the score without improving the artifact. We study the

ThinkFlow: Self-Evolving Probabilistic Latent Memory for Lifelong Conversational Agents

arXiv:2609.17010v1 Announce Type: new Abstract: Lifelong conversational agents rely on memory systems to maintain deep, context-aware interactions with users. However, existing explicit textual memory

ViCo: Visual-oriented Coding with Self-Reflection for Chart Replication

arXiv:2609.16014v1 Announce Type: new Abstract: This paper addresses the challenge of generating high-quality academic charts that match the visual standards of human-authored papers. While existing A

researcharxiv-cs-cl

VPRef: A Cross-Domain Benchmark for Referring Remote Sensing Image Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.16486v1 Announce Type: new Abstract: Rapid advancements in vision-language models have propelled Referring Remote Sensing Image Segmentation (RRSIS) to the forefront of Earth observation. H

Which Pretext Task Transfers? Self-Supervised Pretraining Objectives for Lung Ultrasound

arXiv:2609.16551v1 Announce Type: new Abstract: Self-supervised learning (SSL) can reduce the need for labelled medical images, but the choice of pretext objective remains unclear for lung ultrasound

researcharxiv-cs-cv

3D Gait-Based Autism Classification Using Attention-Enhanced Deep Learning with Cross-Fold Statistical Stability Analysis

model-releasesarxiv-cs-cv

arXiv:2609.14159v1 Announce Type: new Abstract: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition whose early diagnosis remains challenging because conventional clinical assessments are

A Unified Vision-Language Model for PSMA PET/CT Report Generation, Visual Question Answering, and Lesion Segmentation

arXiv:2609.15603v1 Announce Type: cross Abstract: Accurate PSMA PET/CT interpretation is central to prostate cancer management, yet existing PET/CT AI models typically address isolated tasks. We propo

AbFlow : End-to-end Paratope-Centric Antibody Design by Interaction Enhanced Flow Matching

arXiv:2602.07084v2 Announce Type: replace-cross Abstract: Antigen-antibody binding is a critical process in the immune response. Although recent progress has advanced antibody design, current methods

ABSOL: Aggregated Bayesian Subsampling Orchestrated with LLMs

arXiv:2609.15007v1 Announce Type: new Abstract: Large language models are increasingly used as natural-language interfaces to structured data, yet they remain unreliable when answers require consisten

Accelerating Transfer-Learning-Based Autotuning with Predictive LLVM IR Performance Ranking

arXiv:2609.15807v1 Announce Type: cross Abstract: As the complexity of High Performance Computing (HPC) ecosys- tems continually increases, achieving optimal performance becomes a challenge. Tradition

researcharxiv-cs-lg

Accurate and Scalable Multimodal Pathology Retrieval via Attentive Vision-Language Alignment

arXiv:2510.23224v2 Announce Type: replace Abstract: The rapid digitization of histopathology slides has opened new opportunities for computational tools in clinical and research workflows. Content-bas

safetyarxiv-cs-cv

AcquireBound: Runtime Authorization for Resources Acquired by AI Agents

arXiv:2609.14744v1 Announce Type: new Abstract: By acquiring compute, credentials, accounts, services, and other agents, autonomous AI agents can introduce new authority into a task. Payment, budget,

Adaptive Conformal Redistribution for Inter-class Transitional Uncertainty in Medical Image Classification

arXiv:2609.13303v1 Announce Type: cross Abstract: Medical image classification is frequently complicated by transitional categories whose feature distributions overlap those of adjacent classes, produ

AlignUS: MRI-Guided Ultrasound Representation Learning for ALS Classification from Tongue Images

arXiv:2609.15285v1 Announce Type: new Abstract: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease in which early assessment remains challenging, particularly in low-resour

researcharxiv-cs-cv

All Learning Has an Emotional Basis, So Does Task-Oriented Dialogue

arXiv:2507.01594v2 Announce Type: replace Abstract: Task-oriented dialogue (ToD) systems aim to help users accomplish goals through natural language interaction. Beyond task success, effective ToD sys

researcharxiv-cs-cl

An Incomplete Loop: Deductive, Inductive, and Abductive Reasoning in Language Models

arXiv:2404.03028v4 Announce Type: replace Abstract: Modern language models (LMs) can learn to perform new tasks in different ways: in instruction following, the target task is described explicitly in

An Information-Space Perspective to Scene Graph Sufficiency for Robotic Task Planning

arXiv:2609.15587v1 Announce Type: new Abstract: Planning in complex environments requires task specifications grounded in representations that capture objects, relations, and affordances; scene graphs

researcharxiv-cs-ro