Search: “models”

Generated Context versus Governed State: Functional Conditions for Accountable Longitudinal Clinical Reasoning

arXiv:2608.14804v1 Announce Type: new Abstract: Large language models (LLMs) have become the dominant interface of clinical artificial intelligence, yet the interface they expose (text in, text out, o

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

MoE Router-Guided Clustering for Heterogeneous Federated Instruction Tuning

DGX agent

arXiv:2608.15311v1 Announce Type: new Abstract: Federated instruction fine-tuning enables Large Language Models (LLMs) to adapt to decentralized, privacy-sensitive data without requiring data sharing.

model-releasesarxiv-cs-ai

18 Aug 2026

PixRestore: Unified Image Restoration via Pixel Diffusion Transformer

arXiv:2608.16793v1 Announce Type: new Abstract: Unified image restoration (UIR) aims to recover high-quality (HQ) content from low-quality (LQ) images with different degradations using a single model.

Prompting is not enough: supervised baselines and leakage control for measuring shared decision-making with LLMs in pediatric encounters

arXiv:2608.14792v1 Announce Type: cross Abstract: Objectives: To determine whether zero-shot prompting of a large language model (LLM) is sufficient to detect shared decision-making (SDM) behaviors in

The Unwritten Benchmark: A New Challenge for Multimodal Machine Learning in Abstract Perceptual Reasoning

arXiv:2608.14558v1 Announce Type: new Abstract: Current multimodal models have demonstrated remarkable proficiency in recognizing static visual and auditory content. However, their capacity for abstra

The Working Set of a Coding Agent: Coherence Debt in Repository-Scale Tasks

model-releasesarxiv-cs-lg

arXiv:2608.16630v1 Announce Type: cross Abstract: Repository-scale coding requires an agent to keep tests, imports, configuration, and migration rules consistent within a bounded context window. We mo

When State Becomes an Attack Surface: State-Semantic Injection in LLM-Driven Embodied Agents

arXiv:2608.16806v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated capabilities in in-context learning, task decomposition, step-by-step reasoning, and code generation, d

safetyarxiv-cs-ai

When Stories Evolve: Benchmarking LLM Storytelling Across Agent Architectures in Open-Ended World Simulations

arXiv:2608.15654v1 Announce Type: cross Abstract: Large language models can write fluent stories, but open-ended storytelling requires more than local fluency. In evolving world simulations and AI-nat

A Data-Driven Algorithm for Model-Free Control Synthesis

arXiv:2602.13157v2 Announce Type: replace-cross Abstract: Presented is an algorithm to synthesize the optimal infinite-horizon LQR feedback controller for continuous-time systems. The algorithm does n

researcharxiv-cs-ro

A Graph-Based Reinforcement Learning Framework for Structured Drift Diagnosis and Recovery in Autonomous LLM Agents

arXiv:2608.14109v1 Announce Type: new Abstract: Autonomous LLM agents are increasingly deployed in complex real-world workflows, yet they remain vulnerable to runtime behavioral drift, a silent deviat

Detecting Contaminated Code-Generation Prompt Batches via Influence Functions

model-releasesarxiv-cs-lg

arXiv:2608.14303v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for code generation, yet they remain vulnerable to prompts that elicit insecure implementations. Exis

Non-Shattering at and Above the Dynamical Temperature in the Spherical Pure p-Spin Model

arXiv:2608.14369v1 Announce Type: cross Abstract: We consider the notion of shattering introduced by Ben Arous and Jagannath for spherical pure p-spin glasses with overlap q. For every pgeq 3 and 0sqr

researcharxiv-cs-lg

S2Dialog: Multimodal Dialogue Retrieval with Semantic and Acoustic-Style Modeling

arXiv:2608.14029v1 Announce Type: new Abstract: Multimodal dialogue retrieval aims to retrieve dialogues from multimodal dialogue banks that are similar to a target dialogue in terms of both textual s

researcharxiv-cs-cl

Agent Behavioral Contracts II: Certifying Compositional Reliability Without Assuming Independence

arXiv:2608.12895v1 Announce Type: new Abstract: Compositional reliability bounds for multi-agent systems multiply component reliabilities, a step licensed by a conditional-independence assumption that

Learning Under Treatment-Induced Label Indeterminacy with Expert Annotations of Counterfactual Outcomes: A Case Study in Neurological Prognostication

arXiv:2608.12477v1 Announce Type: new Abstract: Clinical prediction models are often developed as if the outcome of interest were cleanly observed for every patient. This assumption fails when treatme

safetyarxiv-cs-lg

Applications

RealMat: Realistic Materials with Diffusion and Reinforcement Learning

arXiv:2509.01134v2 Announce Type: replace-cross Abstract: Generative models for high-quality materials are particularly desirable to make 3D content authoring more accessible. However, the majority of

applicationsarxiv-cs-cv

Rules or Character? Scaling Laws for AI Safety Design

arXiv:2608.13345v1 Announce Type: new Abstract: Artificial Intelligence (AI) safety systems combine character shaping (e.g., Reinforcement Learning from Human Feedback [RLHF], Constitutional AI), whic

Scaling Representation Diversity: Modulated Attention and Reconstructive Regularization for Visual Grounding

arXiv:2608.12748v1 Announce Type: new Abstract: Referring Expression Comprehension (REC) is commonly studied under dataset-specific fine-tuning, resulting in specialist models with limited cross-datas

Agents

SynAct: A Reasoning-Acting Large Language Model Agent for Adaptive Synthesis Optimization

arXiv:2608.12751v1 Announce Type: cross Abstract: Logic synthesis transforms RTL designs into gate-level netlists, where PPA results are highly sensitive to the choice of optimization commands, making

agentsarxiv-cs-ai

DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation

arXiv:2608.11889v1 Announce Type: cross Abstract: Prompting-based (extit{i}.extit{e}., non-fine-tuning) Text-to-SQL methods, where underlying large language model parameters are not changed for the ta

FrontierFinance: A Challenging Benchmark for Measuring Frontier Intelligence of Finance Agents

arXiv:2608.11683v1 Announce Type: new Abstract: AI agents are increasingly deployed for professional investment research, yet no benchmark captures the complexity of the full investor workflow. Existi

G0.5: One Autoregressive Stream for Robot Reasoning and Action

arXiv:2608.11739v1 Announce Type: cross Abstract: The prevailing recipe for Vision-Language-Action (VLA) models couples a pretrained VLM with a separately trained flow-matching action expert. This mak

Information Abundance Paradox: Long-Context Training Undermines Parametric Knowledge

arXiv:2608.12218v1 Announce Type: cross Abstract: Large language models are increasingly trained and deployed with long contexts that span documents, code repositories, and interaction histories. This

Inverse Theory of Mind Modeling for Content Recommendation: From Web Browsing to Dynamic Intelligent Interfaces

arXiv:2608.11354v1 Announce Type: new Abstract: Modern recommender systems treat observed actions as reliable proxies for user preferences, yet interactions often reflect exploration or comparison rat

safetyarxiv-cs-ai

Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning

arXiv:2608.11408v1 Announce Type: new Abstract: Prior white-box studies show that large language models can retain latent traces of target knowledge after unlearning, even when the knowledge is no lon

researcharxiv-cs-cl

Representation Finetuning for Continual Learning

arXiv:2603.11201v3 Announce Type: replace-cross Abstract: The world is inherently dynamic, and continual learning aims to enable models to adapt to ever-evolving data streams. While pre-trained models

Surfsvr: 2D Surface Priors as 3D Geometric Regularizers for Sparse Voxel Reconstruction

arXiv:2608.11938v1 Announce Type: new Abstract: Sparse voxel reconstruction offers an efficient representation for high-fidelity 3D modeling, yet its geometry is commonly optimized from local photomet

The Edge-based Contiguous p-median Problem with Connections to Logistics Districting

arXiv:2608.11230v1 Announce Type: new Abstract: This paper introduces the edge-based contiguous p-median (ECpM) problem to partition the roads in a network into a given number of compact and contiguou

researcharxiv-cs-ai

The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy

arXiv:2607.11175v2 Announce Type: replace Abstract: The growing ability of large language models and vision-language models to jointly interpret and reason over images and text is reshaping medical im

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition

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

Agents

Cross-View Sequential Visual Localization with Spatio-Temporal Context Modeling for Autonomous Driving

arXiv:2608.10660v1 Announce Type: cross Abstract: Continuous and reliable localization is essential for autonomous driving. Cross-view visual localization matches ground images with satellite maps, pr

agentsarxiv-cs-ai

DashArena: Benchmarking LLMs on Interactive Analytic Dashboard Generation

arXiv:2608.10567v1 Announce Type: new Abstract: Analytic dashboards combine coordinated views and interactions for data exploration and decision-making. Recent models can generate them from data and n

FoR-SALE: Frame of Reference-guided Spatial Adjustment in LLM-based Diffusion Editing

arXiv:2509.23452v2 Announce Type: replace-cross Abstract: Current text-to-image generation models, even state-of-the-art models, exhibit a significant performance gap when spatial expressions are desc

safetyarxiv-cs-cl

Generating Attacks for LLMs with GFlowNets

arXiv:2608.10171v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) has facilitated their ubiquitous integration into various domains, leading to widespread adoption.

researcharxiv-cs-ai

SQuaT: Self-Supervised Knowledge Distillation via Student-Aware Quantized Teacher Features

arXiv:2608.10709v1 Announce Type: new Abstract: Quantization-Aware Training (QAT) enables the deployment of quantized models with minimal accuracy degradation. However, in practical scenarios, trainin

researcharxiv-cs-lg

VibeLifeBench: Can Your Life Agent Be Proactive and Persistent in a Living World?

arXiv:2608.10875v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly deployed as personal assistants. Existing evaluations, however, mostly use short, self-contained re

Where To Look? : Causal Tracing of Vision Encoders in VLM

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

researcharxiv-cs-cv

An Expectation-Maximization Perspective on Reinforcement Learning for LLM Reasoning

arXiv:2504.18587v2 Announce Type: replace-cross Abstract: Reinforcement learning has emerged as a powerful approach for improving the reasoning capabilities of large language models, as demonstrated b

BASIS: Breach-Aware Selective Prompt Injection Shielding with Prefill Attention Probes

arXiv:2608.08027v1 Announce Type: cross Abstract: Prompt injection is a critical security threat in large language model (LLM) applications, where attackers hijack model behavior by embedding maliciou

researcharxiv-cs-lg

BDH-CQ: In-Context Learning with Recurrent Latent Reasoning

arXiv:2608.09888v1 Announce Type: cross Abstract: We introduce BDH-CQ, a reasoning model that combines in-context learning with recurrent latent reasoning. Inputs presented at inference time continuou

Build it, Break it, Repeat: Benchmarking and improving LLM-manipulated disinformation detection in social media posts

arXiv:2608.09510v1 Announce Type: cross Abstract: Detecting machine-generated disinformation on social media is increasingly difficult as large language models (LLMs) make it easier to generate and re

Can LLM Agents Stick to the Script? A Benchmark for Long-Horizon Consistency in Interactive Narratives

arXiv:2608.08160v1 Announce Type: cross Abstract: The rapid advancement of Large Language Models (LLMs) is revolutionizing AI for Games by enabling open-ended and fluid interactive storytelling. Howev

DarwinX: Evolving Agent Harnesses Through Natural Selection

arXiv:2608.07545v1 Announce Type: cross Abstract: An LLM agent's capability depends not only on model weights but on its harness: prompts, tools, skills, and control flow. Self-improvement loops alrea

DiffSafeMerge: Mitigating Backdoor Inheritance in Diffusion Model Merging

arXiv:2608.09445v1 Announce Type: cross Abstract: Unconditional diffusion checkpoint merging assumes benign sources, yet a compromised public checkpoint can transfer a dormant backdoor while clean gen

researcharxiv-cs-cv

From Fake to Real: Pretraining on Balanced Synthetic Images to Prevent Spurious Correlations in Image Recognition

arXiv:2308.04553v4 Announce Type: replace Abstract: Visual recognition models are prone to learning spurious correlations induced by a biased training set where certain conditions B (eg, Indoors) are

safetyarxiv-cs-cv

Local Ai

Hallucination-Free GUI Grounding via Regression-Free Layout-Aware Matching

arXiv:2608.09654v1 Announce Type: new Abstract: GUI agents are shifting from metadata-dependent large language models to purely visual multimodal large language models (MLLMs) that operate directly on

local-aiarxiv-cs-ai

LHSDet: High-Resolution AI-Generated Image Detection via Visual Question Answering

arXiv:2608.07863v1 Announce Type: new Abstract: Driven by advances in diffusion models and autoregressive models, the fidelity and resolution of AI-generated images now rival those of real images. How

researcharxiv-cs-cv

LIRA: Local Cross-Layer Information Routing for Vision-Language-Action Decoding

arXiv:2608.07596v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models transform representations from pretrained vision-language models (VLMs) into robot actions, yet the interface that