Search: “framework”

GITCO: Gated Inference-Time Context Optimization in TSFMs

arXiv:2606.05332v1 Announce Type: new Abstract: Patch-based Time Series Foundation Models (TSFMs) suffer from context poisoning: structurally anomalous patches capture disproportionate attention and s

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

How Far Did They Go? The Persuasive Tactics of Covert LLM Agents in a Discontinued Field Experiment

DGX agent

arXiv:2606.05256v1 Announce Type: new Abstract: This study analyzes a publicly released dataset from a discontinued field experiment on Reddit's r/ChangeMyView. The intervention, conducted by unknown,

model-releasesarxiv-cs-ai

6 Jun 2026

Human oversight of agentic systems in practice: Examining the oversight work, challenges, and heuristics of developers using software agents

arXiv:2606.05391v1 Announce Type: cross Abstract: Autonomous software agents hold promise to increase developer productivity but make mistakes and exhibit novel failure modes, making human oversight c

agentsarxiv-cs-ai

Individual Gain, Collective Loss: Metacognitive Adaptation in AI-Assisted Creativity

arXiv:2606.05532v1 Announce Type: new Abstract: Recent studies reveal a paradox: AI enhances individual creative outputs while reducing collective diversity. Current explanations -- cognitive offloadi

Knowledge Activation: AI Skills as the Institutional Knowledge Primitive for Agentic Software Development

arXiv:2603.14805v2 Announce Type: replace Abstract: Enterprise software organizations accumulate critical institutional knowledge - architectural decisions, deployment procedures, compliance policies,

agentsarxiv-cs-ai

Learning What Matters: Probabilistic Task Selection via Mutual Information for Model Finetuning

arXiv:2507.12612v3 Announce Type: replace-cross Abstract: Supervised fine-tuning performance for large language models depends strongly on how training budget is distributed across a heterogeneous set

Memory is Reconstructed, Not Retrieved: Graph Memory for LLM Agents

arXiv:2606.06036v1 Announce Type: new Abstract: Despite recent progress, LLM agents still struggle with reasoning over long interaction histories. While current memory-augmented agents rely on a stati

Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models

arXiv:2606.05429v1 Announce Type: new Abstract: Post-training quantization (PTQ) is critical for the efficient deployment of large language models (LLMs). Recent ultra-low-bit PTQ methods rely on rigi

Multi-ResNets for Subspace Preconditioning in Constrained Optimization

arXiv:2606.06300v1 Announce Type: new Abstract: We propose MResOpt, a staged residual neural network architecture for constrained optimization problems. Our architecture fits within predict-complete-c

Multilingual Fine-Tuning via Localized Gradient Conflict Resolution

arXiv:2606.05613v1 Announce Type: new Abstract: The rapid evolution of Large Language Models (LLMs) has established cross-lingual versatility as a defining feature of modern systems. However, fine-tun

Local Ai

Ontology-constrained multi-LLM scoring of hypothesis support in the predictive processing literature

arXiv:2606.05206v1 Announce Type: cross Abstract: Fragmentation is common in interdisciplinary fields with diverse methods and theoretical commitments. Predictive coding neuroscience is a clear exampl

local-aiarxiv-cs-ai

PAMF: Prior-Aware Multimodal Fusion for Incomplete Time Series Data

arXiv:2606.06328v1 Announce Type: cross Abstract: In healthcare, multimodal time series tasks often operate on incomplete observations in practice, for example when ECG segments are lost because elect

applicationsarxiv-cs-ai

PerceptUI: LLM Agents as Human-Aligned Synthetic Users for UI/UX Evaluation

arXiv:2606.05697v1 Announce Type: new Abstract: User interface (UI) and user experience (UX) evaluation is central to product development, yet reliable feedback still relies on recruiting human partic

Plug-and-Play Guidance for Discrete Diffusion Models via Gradient-Informed Logit Correction

arXiv:2606.06303v1 Announce Type: cross Abstract: Controllable generation with discrete diffusion models is often hindered by high computational overhead or the need for retraining. In this paper, we

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows

arXiv:2605.12376v2 Announce Type: replace Abstract: Table processing-including cleaning, transformation, augmentation, and matching-is a foundational yet error-prone stage in real-world data pipelines

RAG Security and Privacy: Formalizing the Threat Model and Attack Surface

arXiv:2509.20324v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) is an emerging approach in natural language processing that combines large language models (LLMs) with ex

applicationsarxiv-cs-ai

Reformulating Neural Operators in d+1 Dimensions for Embedding Evolution

arXiv:2505.11766v4 Announce Type: replace-cross Abstract: Neural Operators (NOs) are powerful architectures for learning mappings between function spaces. While most advances focus on refining kernel

Reward-Decomposed Reinforcement Learning for Immersive Video Role-Playing

arXiv:2605.04733v2 Announce Type: replace Abstract: Text-based role-playing models can imitate character styles, but often fail to capture scene atmosphere and evolving tension, which are crucial for

SAGE: Scalable AI Governance & Evaluation

arXiv:2602.07840v3 Announce Type: replace-cross Abstract: Evaluating relevance in large-scale search systems is fundamentally constrained by the governance gap between nuanced, resource-constrained hu

Towards Healthy Evolution: Exploring the Role and Mechanisms of Human-Agent Interaction in Self-Evolving Systems

arXiv:2606.06114v1 Announce Type: new Abstract: Self-evolving agents improve through continual self-play and self-generated learning signals, but autonomous evolution can also cause capability degrada

Towards the Readability of LLM-Generated Codes through Multitask Representation Engineering

arXiv:2606.06214v1 Announce Type: cross Abstract: Correctness and readability are key measures of code quality, respectively ensuring functional fidelity and ease of comprehension. While most existing

Towards Unified and Data-Efficient Prognostics and Health Management with Tabular Foundation Models

arXiv:2606.05481v1 Announce Type: cross Abstract: Data-driven Prognostics and Health Management (PHM) uses time-varying condition-monitoring data to diagnose system states and estimate remaining usefu

Towards World Models in Biomedical Research

arXiv:2606.05925v1 Announce Type: new Abstract: A central goal of biomedicine is to understand, predict and ultimately control the dynamic mechanisms by which biological systems respond to perturbatio

Uncertainty Aware Functional Behavior Prediction and Material Fatigue Assessment for Circular Factory

arXiv:2606.05334v1 Announce Type: new Abstract: Returned products in circular factories re-enter production with heterogeneous degradation states, usage histories, and remaining capability. Reuse cann

applicationsarxiv-cs-ai

UniVoice: A Unified Model for Speech and Singing Voice Generation

arXiv:2606.05852v1 Announce Type: cross Abstract: Text-to-speech (TTS) and singing voice synthesis (SVS) both aim to generate human vocal audio from symbolic inputs, but they impose different requirem

Updated the skills hub integration search in the Hermes Agent Dashboard to be way more comprehensive and give you the info you need.

The Hermes Agent Dashboard's skills hub integration search functionality has been enhanced to provide more comprehensive results and improved information delivery to users. This update, shared by Nous

agentsnous-research--x

WorldFly: A World-Model-Based Vision-Language-Action Model for UAV Navigation

arXiv:2606.06147v1 Announce Type: new Abstract: End-to-end Vision-Language-Action (VLA) models have shown promise in UAV navigation. However, existing approaches typically rely on historical observati

X-Band UAV-enabled Integrated Sensing and Communications for Vehicular Networks

arXiv:2606.05262v1 Announce Type: cross Abstract: Uncrewed aerial vehicles (UAVs) are increasingly considered as aerial platforms capable of providing both sensing and communication services, represen

3D Underwater Path Planning via Generative Flow Field Surrogates

model-releasesarxiv-cs-ro

arXiv:2606.06077v1 Announce Type: new Abstract: Autonomous underwater vehicle (AUV) launch and recovery (LAR) into the hull of an advancing host platform requires traversal of a complex, three-dimensi

ABBEL: Learning Natural-Language Belief States for Memory-Efficient Interaction

arXiv:2512.20111v2 Announce Type: replace Abstract: As the time horizons of sequential decision-making tasks grow, keeping full interaction histories in model context becomes increasingly costly. Rece

agentsarxiv-cs-cl

Hardware

Accelerating and Scaling MPC-Guided Reinforcement Learning for Humanoid Locomotion and Manipulation

arXiv:2606.05687v1 Announce Type: new Abstract: In humanoid motion control, model predictive control (MPC) offers physically grounded prediction and constraint handling, while reinforcement learning (

hardwarearxiv-cs-ro

ACE-SQL: Adaptive Co-Optimization via Empirical Credit Assignment for Text-to-SQL

arXiv:2606.05906v1 Announce Type: new Abstract: Text-to-SQL maps natural language questions to executable SQL queries. Modern databases often contain large and complex schemas, making schema linking a

safetyarxiv-cs-cl

Activation-Informed Pareto-Guided Low-Rank Compression for Efficient LLM/VLM

arXiv:2510.05544v2 Announce Type: replace Abstract: Large language models (LLM) and vision-language models (VLM) have achieved state-of-the-art performance, but they impose significant memory and comp

researcharxiv-cs-cl

ActiveMimic: Egocentric Video Pretraining with Active Perception

arXiv:2606.06194v1 Announce Type: cross Abstract: Egocentric human video offers a scalable alternative to robot data for pretraining, yet models pretrained on such video consistently underperform thos

applicationsarxiv-cs-cv

Adaptive Tokenisation Via Temporal Redundancy Masking And Latent Inpainting

model-releasesarxiv-cs-cv

arXiv:2606.06158v1 Announce Type: new Abstract: Adaptive video tokenisation seeks to dynamically allocate token budgets based on the underlying visual complexity of a sequence. Current continuous-regi

Adversarial Attacks Already Tell the Answer: Directional Bias-Guided Test-time Defense for Vision-Language Models

arXiv:2606.06186v1 Announce Type: new Abstract: Vision-Language Models (VLMs), such as CLIP, have shown strong zero-shot generalization but remain highly vulnerable to adversarial perturbations, posin

safetyarxiv-cs-cv

Local Ai

AffordanceVLA: A Vision-Language-Action Model Empowering Action Generation through Affordance-Aware Understanding

arXiv:2606.06155v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models leverage the rich world knowledge of pretrained vision-language models (VLMs) to enable instruction-following robo

local-aiarxiv-cs-cv

Asuka-Bench: Benchmarking Code Agents on Underspecified User Intent and Multi-Round Refinement

model-releasesarxiv-cs-cl

arXiv:2606.05920v1 Announce Type: cross Abstract: Existing code-generation benchmarks score a single mapping from a complete prompt to a one-shot output. However, real web development is different. Us

Local Ai

b9535

local-aillama-cpp-releases

The search did not return specific details about the b9535 release. Based on the available information, b9535 is an intermediate build version from the llama.cpp project, which is a C/C++ implementati

Benchmarking Open-Source Layout Detection Models for Data Snapshot Extraction from Institutional Documents

model-releasesarxiv-cs-cl

arXiv:2606.06242v1 Announce Type: new Abstract: Institutional documents contain substantial amounts of operational and analytical information embedded within figures and tables. Current approaches for

Better Literary Translation: A Multi-Aspect Data Generation and LLM Training Approach

model-releasesarxiv-cs-cl

arXiv:2606.05924v1 Announce Type: new Abstract: Literary translation poses unique challenges due to the scarcity of high-quality annotated data and the need to balance expression fluency with literary

Beyond Absolute Scores: Relative Edit-induced Difference for Generalizable Image Aesthetic Assessment

arXiv:2606.05778v1 Announce Type: new Abstract: Traditional Image Aesthetic Assessment (IAA) methods mainly rely on regressing absolute Mean Opinion Scores (MOS). However, such a paradigm overlooks th

researcharxiv-cs-cv

Biomazon: A Multimodal Dataset for 3D Forest Structure and Biomass Modeling in the Amazon Basin

model-releasesarxiv-cs-cv

arXiv:2606.05368v1 Announce Type: new Abstract: Accurate, spatially explicit characterization of tropical forest structure is essential for carbon accounting and ecosystem monitoring, yet most ML pipe

BRepCLIP: Contrastive Multimodal Pretraining on BRep Primitives for CAD Understanding

arXiv:2606.05515v1 Announce Type: new Abstract: Learning representations of CAD models is a largely open problem. While 3D representation learning has flourished around point clouds and meshes, the na

researcharxiv-cs-cv

CamFlow+: Hybrid Motion Bases for 2D Camera Motion Estimation with Stabilization Applications

model-releasesarxiv-cs-cv

arXiv:2606.05915v1 Announce Type: new Abstract: Estimating 2D camera motion is fundamental to computer vision and computational photography. Existing homography-based methods work well for planar scen

ChartAttack: Testing the Vulnerability of LLMs to Malicious Prompting in Chart Generation

arXiv:2601.12983v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) are increasingly used to automate chart generation from data tables, improving analysis and reporting effic

researcharxiv-cs-cl

CHASE: Adversarial Red-Blue Teaming for Improving LLM Safety using Reinforcement Learning

arXiv:2606.05523v1 Announce Type: new Abstract: Despite advances in safety alignment, prompt-rewriting attacks such as persona modulation, fictional framing and persuasion-based reformulation, can byp

safetyarxiv-cs-cl

CLEAR: Cognition and Latent Evaluation for Adaptive Routing in End-to-End Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2606.06219v1 Announce Type: new Abstract: End-to-end autonomous driving models often struggle to balance multi-modal maneuver generation with real-time inference constraints. While diffusion mod