Search: “agents”

Value Explicit Pretraining for Learning Transferable Representations

model-releasesarxiv-cs-lg

arXiv:2312.12339v3 Announce Type: replace Abstract: Understanding visual inputs for a given task amidst varied changes is a key challenge posed by visual reinforcement learning agents. We propose exti

4 May 2026

Attractor FCM

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arXiv:2604.27947v1 Announce Type: cross Abstract: In this paper an attractor FCM is created, tested, and analyzed. This FCM is neither a hebbian based nor agentic, nor a hybrid; it rather is a gradien

local-aiarxiv-cs-ai

1 May 2026

D3-Gym: Constructing Real-World Verifiable Environments for Data-Driven Discovery

arXiv:2604.27977v1 Announce Type: new Abstract: Despite recent progress in language models and agents for scientific data-driven discovery, further advancing their capabilities is held back by the abs

Detecting is Easy, Adapting is Hard: Local Expert Growth for Visual Model-Based Reinforcement Learning under Distribution Shift

arXiv:2604.27411v1 Announce Type: new Abstract: Visual model-based reinforcement learning (MBRL) agents can perform well on the training distribution, but often break down once the test environment sh

local-aiarxiv-cs-lg

Hardware

EdgeFM: Efficient Edge Inference for Vision-Language Models

arXiv:2604.27476v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated strong applicability in edge industrial applications, yet their deployment remains severely constrained

hardwarearxiv-cs-cv

Tutorials

Graph World Models: Concepts, Taxonomy, and Future Directions

arXiv:2604.27895v1 Announce Type: new Abstract: As one of the mainstream models of artificial intelligence, world models allow agents to learn the representation of the environment for efficient predi

tutorialsarxiv-cs-ai

Learning to Forget: Continual Learning with Adaptive Weight Decay

model-releasesarxiv-cs-lg

arXiv:2604.27063v1 Announce Type: new Abstract: Continual learning agents with finite capacity must balance acquiring new knowledge with retaining the old. This requires controlled forgetting of knowl

NashPG: A Policy Gradient Method with Iteratively Refined Regularization for Finding Nash Equilibria

model-releasesarxiv-cs-lg

arXiv:2510.18183v2 Announce Type: replace Abstract: Finding Nash equilibria in two-player zero-sum imperfect-information games remains a central challenge in multi-agent reinforcement learning. Recent

Research

Simulating Infant First-Person Sensorimotor Experience via Motion Retargeting from Babies to Humanoids

arXiv:2604.27583v1 Announce Type: cross Abstract: Motion retargeting from humans to human-like artificial agents is becoming increasingly important as humanoid robots grow more capable. However, most

researcharxiv-cs-ro

What Suppresses Nash Equilibrium Play in Large Language Models? Mechanistic Evidence and Causal Control

arXiv:2604.27167v1 Announce Type: cross Abstract: LLM agents are known to deviate from Nash equilibria in strategic interactions, but nobody has looked inside the model to understand why, or asked whe

Research

A Decision-Theoretic Formalisation of Steganography With Applications to LLM Monitoring

arXiv:2602.23163v3 Announce Type: replace Abstract: Large language models are beginning to show steganographic capabilities. Such capabilities could allow misaligned models to evade oversight mechanis

researcharxiv-cs-ai

Research

Beyond Screenshots: Evaluating VLMs' Understanding of UI Animations

arXiv:2604.26148v1 Announce Type: cross Abstract: AI agents operating on user interfaces must understand how interfaces communicate state and feedback to act reliably. As a core communicative modality

researcharxiv-cs-cl

Distill-Belief: Closed-Loop Inverse Source Localization and Characterization in Physical Fields

arXiv:2604.26095v1 Announce Type: new Abstract: {Closed-loop inverse source localization and characterization (ISLC) requires a mobile agent to select measurements that localize sources and infer late

Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation

arXiv:2511.20714v2 Announce Type: replace-cross Abstract: World models serve as core simulators for fields such as agentic AI, embodied AI, and gaming, capable of generating long, physically realistic

LLM Psychosis: A Theoretical and Diagnostic Framework for Reality-Boundary Failures in Large Language Models

arXiv:2604.25934v1 Announce Type: cross Abstract: The deployment of large language models (LLMs) as interactive agents has exposed a category of behavioral failure that prevailing terminology, princip

Thinking About Thinking: Evaluating Reasoning in Post-Trained Language Models

arXiv:2510.16340v2 Announce Type: replace Abstract: Recent advances in post-training techniques have endowed Large Language Models (LLMs) with enhanced capabilities for tackling complex, logic-intensi

29 Apr 2026

Benchmarking Source-Sensitive Reasoning in Turkish: Humans and LLMs under Evidential Trust Manipulation

arXiv:2604.24665v1 Announce Type: cross Abstract: This paper investigates whether source trustworthiness shapes Turkish evidential morphology and whether large language models (LLMs) track this sensit

Domain-Filtered Knowledge Graphs from Sparse Autoencoder Features

arXiv:2604.23829v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) extract millions of interpretable features from a language model, but flat feature inventories aren't very useful on their ow

Evaluating whether AI models would sabotage AI safety research

arXiv:2604.24618v1 Announce Type: new Abstract: We evaluate the propensity of frontier models to sabotage or refuse to assist with safety research when deployed as AI research agents within a frontier

Grammar-Constrained Refinement of Safety Operational Rules Using Language in the Loop: What Could Go Wrong

arXiv:2604.23523v1 Announce Type: cross Abstract: Safety specifications in cyber-physical systems (CPS) capture the operational conditions the system must satisfy to operate safely within its intended

InCoM: Intent-Driven Perception and Structured Coordination for Mobile Manipulation

arXiv:2602.23024v2 Announce Type: replace Abstract: Mobile manipulation is a fundamental capability for general-purpose robotic agents, requiring both coordinated control of the mobile base and manipu

safetyarxiv-cs-ro

IndustryAssetEQA: A Neurosymbolic Operational Intelligence System for Embodied Question Answering in Industrial Asset Maintenance

arXiv:2604.23446v1 Announce Type: new Abstract: Industrial maintenance environments increasingly rely on AI systems to assist operators in understanding asset behavior, diagnosing failures, and evalua

Intervention-Aware Multiscale Representation Learning from Imaging Phenomics and Perturbation Transcriptomics

arXiv:2604.22832v1 Announce Type: cross Abstract: Microscopy-based phenotypic profiling is scalable for drug discovery but lacks the mechanistic depth of transcriptomics, which remains costly and scar

Learning Selective LLM Autonomy from Copilot Feedback in Enterprise Customer Support Workflows

arXiv:2604.23855v1 Announce Type: new Abstract: We present a deployed system that automates end-to-end customer support workflows inside an enterprise Business Process Management (BPM) platform. The a

RAT: RunAnyThing via Fully Automated Environment Configuration

arXiv:2604.23190v1 Announce Type: cross Abstract: Automating repository-level software engineering tasks is a foundational challenge for autonomous code agents, largely due to the difficulty of config

SMP: Reusable Score-Matching Motion Priors for Physics-Based Character Control

arXiv:2512.03028v3 Announce Type: replace-cross Abstract: Data-driven motion priors that can guide agents toward producing naturalistic behaviors play a pivotal role in creating life-like virtual char

Tutorials

Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions

arXiv:2512.20831v2 Announce Type: replace Abstract: Real-world sequential decision-making often involves parameterized action spaces that require both, decisions regarding discrete actions and decisio

tutorialsarxiv-cs-ai

27 Apr 2026

When Does LLM Self-Correction Help? A Control-Theoretic Markov Diagnostic and Verify-First Intervention

arXiv:2604.22273v1 Announce Type: new Abstract: Iterative self-correction is widely used in agentic LLM systems, but when repeated refinement helps versus hurts remains unclear. We frame self-correcti

27 Apr 2026

Do MLLMs Understand Pointing? Benchmarking and Enhancing Referential Reasoning in Egocentric Vision

model-releasesarxiv-cs-cv

arXiv:2604.21461v1 Announce Type: new Abstract: Egocentric AI agents, such as smart glasses, rely on pointing gestures to resolve referential ambiguities in natural language commands. However, despite

Frozen LLMs as Map-Aware Spatio-Temporal Reasoners for Vehicle Trajectory Prediction

arXiv:2604.21479v1 Announce Type: new Abstract: Large language models (LLMs) have recently demonstrated strong reasoning capabilities and attracted increasing research attention in the field of autono

local-aiarxiv-cs-cv

Hyperloop Transformers

model-releasesarxiv-cs-cl

arXiv:2604.21254v1 Announce Type: cross Abstract: LLM architecture research generally aims to maximize model quality subject to fixed compute/latency budgets. However, many applications of interest su

Inferring High-Level Events from Timestamped Data: Complexity and Medical Applications

arXiv:2604.21793v1 Announce Type: new Abstract: In this paper, we develop a novel logic-based approach to detecting high-level temporally extended events from timestamped data and background knowledge

Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding

arXiv:2604.21268v1 Announce Type: cross Abstract: Graphical User Interface (GUI) grounding requires mapping natural language instructions to precise pixel coordinates. However, due to visually homogen

Rectified Schrodinger Bridge Matching for Few-Step Visual Navigation

arXiv:2604.05673v2 Announce Type: replace-cross Abstract: Visual navigation is a core challenge in Embodied AI, requiring autonomous agents to translate high-dimensional sensory observations into cont

Reinforcing 3D Understanding in Point-VLMs via Geometric Reward Credit Assignment

model-releasesarxiv-cs-cv

arXiv:2604.21160v1 Announce Type: new Abstract: Point-Vision-Language Models promise to empower embodied agents with executable spatial reasoning, yet they frequently succumb to geometric hallucinatio

Reinforcing privacy reasoning in LLMs via normative simulacra from fiction

arXiv:2604.20904v1 Announce Type: cross Abstract: Information handling practices of LLM agents are broadly misaligned with the contextual privacy expectations of their users. Contextual Integrity (CI)

DRIV-EX: Counterfactual Explanations for Driving LLMs

arXiv:2603.00696v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as reasoning engines in autonomous driving, yet their decision-making remains opaque. We propose

EmbodiedMidtrain: Bridging the Gap between Vision-Language Models and Vision-Language-Action Models via Mid-training

arXiv:2604.20012v1 Announce Type: cross Abstract: Vision-Language-Action Models (VLAs) inherit their visual and linguistic capabilities from Vision-Language Models (VLMs), yet most VLAs are built from

Frictionless Love: Associations Between AI Companion Roles and Behavioral Addiction

arXiv:2604.20011v1 Announce Type: cross Abstract: AI companion chatbots increasingly shape how people seek social and emotional connection, sometimes substituting for relationships with romantic partn

Rethinking Reinforcement Fine-Tuning in LVLM: Convergence, Reward Decomposition, and Generalization

arXiv:2604.19857v1 Announce Type: cross Abstract: Reinforcement fine-tuning with verifiable rewards (RLVR) has emerged as a powerful paradigm for equipping large vision-language models (LVLMs) with ag

SciCoQA: Quality Assurance for Scientific Paper--Code Alignment

arXiv:2601.12910v3 Announce Type: replace-cross Abstract: Discrepancies between scientific papers and their code undermine reproducibility, a concern that grows as automated research agents scale scie

Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation

arXiv:2604.20749v1 Announce Type: new Abstract: Situated conversational recommendation (SCR), which utilizes visual scenes grounded in specific environments and natural language dialogue to deliver co

WorkflowGen:an adaptive workflow generation mechanism driven by trajectory experience

arXiv:2604.19756v1 Announce Type: cross Abstract: Large language model (LLM) agents often suffer from high reasoning overhead, excessive token consumption, unstable execution, and inability to reuse p

Benchmarking Misuse Mitigation Against Covert Adversaries

arXiv:2506.06414v2 Announce Type: replace-cross Abstract: Existing language model safety evaluations focus on overt attacks and low-stakes tasks. In reality, an attacker can easily subvert existing sa

Evaluating Answer Leakage Robustness of LLM Tutors against Adversarial Student Attacks

arXiv:2604.18660v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in education, yet their default helpfulness often conflicts with pedagogical principles. Prior work

Hybrid Task and Motion Planning with Reactive Collision Handling for Multi-Robot Disassembly of Complex Products: Application to EV Batteries

arXiv:2509.21020v2 Announce Type: replace Abstract: This paper addresses the problem of multi-robot coordination for complex manipulation task sequences. We present a vision-driven task-and-motion pla

safetyarxiv-cs-ro

Applications

InHabit: Leveraging Image Foundation Models for Scalable 3D Human Placement

arXiv:2604.19673v1 Announce Type: new Abstract: Training embodied agents to understand 3D scenes as humans do requires large-scale data of people meaningfully interacting with diverse environments, ye

applicationsarxiv-cs-cv

Machine individuality: Separating genuine idiosyncrasy from response bias in large language models

arXiv:2604.16755v2 Announce Type: replace Abstract: As large language models (LLMs) are increasingly integrated into daily life, in roles ranging from high-stakes decision support to companionship, un