Search: “context”

Evolutionary Stability Does Not Guarantee Learning Accessibility: A Multi-Agent Reinforcement Learning Perspective on Cooperation Emergence

arXiv:2609.27664v1 Announce Type: new Abstract: Cooperation emergence is a central problem in multi-agent systems because decentralized agents must coordinate while adapting to the changing behavior o

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Model Releases

Harness as a Language: A Minimalist Agent Framework With Maximal Expressivity

DGX agent

arXiv:2609.26891v1 Announce Type: new Abstract: Modern language-model agents are built around the extit{agent loop}, where the LLM is placed in an environment exposing a set of tools, and the LLM has

model-releasesarxiv-cs-ai

24 Sept 2026

Applications

InsurTech innovation using natural language processing

arXiv:2507.21112v4 Announce Type: replace Abstract: With the rapid rise of InsurTech, traditional insurance companies are increasingly exploring alternative data sources and advanced technologies to s

applicationsarxiv-cs-cl

Learning from Failures: Heterogeneous Graph Memory for Small Language Model Tool-Using Agents

arXiv:2609.28003v1 Announce Type: new Abstract: Small and medium-sized language models offer cost-effective executors for tool-using agents, making them attractive for local and large-scale deployment

safetyarxiv-cs-lg

Applications

LiAM-SAM: Lifecycle-Aware Memory for Robust SAM2-Based MOT

arXiv:2609.28078v1 Announce Type: new Abstract: Segmentation-based multi-object tracking (MOT) with foundation video models such as SAM2 offers strong localization quality, yet remains fragile in crow

applicationsarxiv-cs-cv

Multi-View Fusion for Encrypted C2 Detection: A Leakage-Controlled Measurement Study of Evaluation Pitfalls

arXiv:2609.27311v1 Announce Type: cross Abstract: Command-and-control (C2) traffic increasingly hides within TLS, so defenders now apply machine learning to traffic metadata. Many studies assume that

NavProbe: Evidence-Grounded Reasoning with Active Memory Retrieval for Zero-Shot Navigation

arXiv:2609.27526v1 Announce Type: new Abstract: Long-horizon navigation requires an agent to revise its intermediate objectives as evidence accumulates. Full visual histories are costly to process, wh

safetyarxiv-cs-ro

Omni-Decision: Evidence-Ledger Planning for Omni-Modal Agents

model-releasesarxiv-cs-ai

arXiv:2607.11433v2 Announce Type: replace Abstract: Omni-modal agents must seek evidence across video, audio, web pages, and computation to answer questions. Their main bottleneck is planning: noisy m

Safety Nudges: User-Facing Interventions for Real-Time AI Risk Awareness

arXiv:2609.26865v1 Announce Type: cross Abstract: Conversational AI systems can pose safety risks to their users such as hallucination, sycophancy, overconfidence, and anthropomorphism, but these risk

safetyarxiv-cs-ai

Self-Improvement as Coherence Optimization: A Theoretical Account

arXiv:2601.13566v2 Announce Type: replace-cross Abstract: Can language models improve their accuracy without external supervision? Methods such as debate, bootstrap, and internal coherence maximizatio

Shutdown Sabotage Propensities in Multi-Agent Systems

arXiv:2609.28274v1 Announce Type: new Abstract: The final safeguard against rogue AI behavior is the human ability to shut systems down. It has been theorized that when an AI is instructed to perform

Small Cues, Big Consequences: Learning Pivotal Cues for Multimodal Meme Classification

arXiv:2609.26907v1 Announce Type: cross Abstract: Memes often derive their harmful, hateful, or sarcastic meaning from small but decisive visual, textual, or cross-modal cues. Existing multimodal clas

Tutorials

Task-Prototype Guided Flow Matching for Few-Shot Generalization in Vision-Language Robot Manipulation

arXiv:2609.27780v1 Announce Type: cross Abstract: Vision-language robot manipulation policies can follow semantic instructions, but adapting them to a new procedure from only a few demonstrations rema

tutorialsarxiv-cs-cv

The Like Trap: Multi-Stage Poisoning against Agents in Similarity-based Recommendation Systems

arXiv:2609.27155v1 Announce Type: cross Abstract: With recent advancements in large language models (LLMs) and LLM-based agents, these agents are becoming increasingly autonomous and gaining broader a

Training Intelligent Voice Assistant Wakeup with Controllable Synthetic Conversations

arXiv:2609.27037v1 Announce Type: new Abstract: Wake word detection is a critical component of virtual assistants, serving as the gateway to seamless user interactions. This paper introduces a novel w

VMMU: A Vietnamese Multitask Multimodal Understanding and Reasoning Benchmark

arXiv:2508.13680v5 Announce Type: replace Abstract: We introduce VMMU, a Vietnamese Multitask Multimodal Understanding and Reasoning Benchmark designed to evaluate how vision-language models (VLMs) in

What Makes a Terminal-Bench Task Hard? Separating Genuine Hardness from Fake-Hardness on an Adjudicated Agentic Corpus

arXiv:2609.26826v1 Announce Type: cross Abstract: Frontier benchmarks need tasks that current models cannot solve. But a task that no model solves is not automatically a hard task. The same zero pass

Zero-Shot Object Removal via Attention Masking, Latent Anchoring, and Refinement

arXiv:2609.28342v1 Announce Type: new Abstract: Removing an object from a real image requires more than synthesizing plausible content within a mask: the method must suppress residual object features,

A Lean and Spec-Driven AI-Assisted Software Development Lifecycle for Applied AI Education: The AI-SDLC Approach

arXiv:2609.24348v1 Announce Type: cross Abstract: AI coding agents increasingly support software development beyond code completion, including planning, implementation, testing, and repository-level t

local-aiarxiv-cs-ai

ABAI at COLIEE 2026 Task 1: Multi-Stage Retrieval with GraphRAG-Enhanced Meta-Learning, and a Post-Hoc Study of the Cross-Validation-to-Test Gap

arXiv:2609.26237v1 Announce Type: cross Abstract: We present the ABAI submission to COLIEE 2026 Task 1, case law retrieval, together with a controlled study of why it underperformed. The task suppress

researcharxiv-cs-cl

ActGov: Governing LLM Agent Actions via Policy-Constrained Validation

arXiv:2609.24446v2 Announce Type: cross Abstract: Large language model (LLM) agents increasingly execute long-horizon workflows through external tools, allowing untrusted outputs to influence subseque

safetyarxiv-cs-ai

Brain-Token Learning: Microstate-Based Tokenization and Multi-Scale Interaction for Long-Horizon EEG Sequence Modeling

arXiv:2609.24324v1 Announce Type: new Abstract: Electroencephalography (EEG) provides a non-invasive window into dynamic brain activity, yet modeling long-horizon EEG sequences remains challenging due

CableVLA: Simulation-Privileged Global-Local Representation Learning for Cable Routing

model-releasesarxiv-cs-ro

arXiv:2609.25606v1 Announce Type: new Abstract: Cable routing requires coordinated control of global cable topology and changing local contacts. We present CableVLA, an end-to-end multimodal vision-la

Cellular-Communication-Level Interpretability for Pathology Foundation Models via Graph Distillation on Microenvironment

arXiv:2609.26073v1 Announce Type: new Abstract: Pathology foundation models (PFMs) provide strong tile-level representations but remain difficult to interpret at the cellular and microenvironmental sc

CricRAG: Retrieval Augmented Vision-Language Models for Personalized Cricket Coaching

arXiv:2609.26056v1 Announce Type: new Abstract: Vision-Language Models (VLMs) offer promising capabilities for automated sports coaching but face a fundamental limitation: they implicitly compare agai

safetyarxiv-cs-cv

Deepfakes and Synthetic Media: Generation, Detection, and Governance

arXiv:2609.25017v1 Announce Type: new Abstract: Deepfakes, synthetic audiovisual content produced by deep generative models, have escalated into a critical threat across civilian and military domains,

safetyarxiv-cs-cv

Discrete vs. Continuous: A Comprehensive Study of Unified Audio Understanding in LALMs

model-releasesarxiv-cs-ai

arXiv:2609.22851v2 Announce Type: cross Abstract: Large Audio Language Models (LALMs) utilize either continuous features or discrete tokens, yet the optimal representation paradigm for general audio u

DreamStream: Towards Policy-Oriented Generative Simulation for End-to-End Driving

model-releasesarxiv-cs-ro

arXiv:2609.26792v1 Announce Type: new Abstract: Faithfully evaluating end-to-end driving policies in simulation requires observations that are not merely photo-realistic, but preserve the scene featur

Epi-Logic: A Conceptual Framework for Epistemic Runtime Control, Schema Validity Checking, and Controlled Accommodation in Autonomous AI Agents

arXiv:2609.24755v1 Announce Type: new Abstract: Autonomous AI agents are increasingly deployed in areas where wrong decisions are hard to reverse. This paper examines schema mismatch: the condition in

Evaluating Accuracy and Probabilistic Reliability of Zero-Shot Time Series Foundation Models

model-releasesarxiv-cs-lg

arXiv:2609.25788v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) promise a paradigm shift toward zero-shot forecasting by eliminating task-specific training. However, existing wor

From Token Importance to Conditional Removability: Rethinking Visual Token Pruning in Multimodal Large Language Models

arXiv:2609.26484v1 Announce Type: new Abstract: Training-free visual-token pruning often uses token importance, redundancy, or related selection criteria as proxies for safe removal. We show that thes

From Utterances to Networks: Modelling Slang Adoption and Diffusion Across Subreddits

arXiv:2609.25669v1 Announce Type: new Abstract: Adoption and diffusion of neologisms in online communities have received renewed attention in recent years. As internet slang terms such as APT, referri

Fysiverse-3D-Vision Technical Report: Generating Executable 3D Worlds from Images through Unified Spatial Reasoning

arXiv:2609.25741v1 Announce Type: new Abstract: Generative models have advanced image-conditioned 3D content creation, yet generating controllable and executable 3D scenes from a single image remains

safetyarxiv-cs-cv

Generative Embodied Multiple Behavior Control Systems for Human-like Agents

arXiv:2609.22691v1 Announce Type: new Abstract: An enduring and richly elaborated dichotomy in cognitive neuroscience is that of human behavior control mechanisms, divided into habitual versus goal-di

Geometric and Semantic Coupling for Interaction Understanding in 3D Scenes

arXiv:2609.25247v1 Announce Type: new Abstract: Interaction understanding in 3D scenes requires a joint description of movable parts, their motion, and the regions through which they can be operated.

Goal-driven Variant Categorization

arXiv:2609.22475v1 Announce Type: new Abstract: Process discovery rarely yields a single coherent process structure. For analysis, a common step is to cluster process variants based on structural simi

Hapi: A Multivariable Land-Surface Transformer for Medium-Range Hydrological Forecasting at Continental Scale

arXiv:2609.22702v1 Announce Type: new Abstract: Accurate flood forecasts several days in advance are essential for flood control, water-resource management, and emergency response. Producing them at h

local-aiarxiv-cs-ai

Higher-Order Approximation of Exit Functionals in Sampling-Based Stochastic Model Predictive Control

arXiv:2609.25257v1 Announce Type: cross Abstract: Safety evaluation in sampling-based stochastic model predictive control often requires numerical estimation of exit functionals. The approximation of

safetyarxiv-cs-ro

Imperfection for Precision: Upcycling Imperfect Data for High-Precision Robotic Manipulation

arXiv:2609.26672v1 Announce Type: new Abstract: Training vision-language-action (VLA) models for high-precision manipulation typically requires task-specific, high-quality data (e.g., teleoperation),

safetyarxiv-cs-ro

Latest Exact Match Attention

arXiv:2609.25802v1 Announce Type: cross Abstract: We introduce latest exact match attention (LEMA), an attention variant for transformers where queries and keys are binarized and each query attends on

local-aiarxiv-cs-cl

Learning to Defer with Guidance on Real World Medical Data

arXiv:2609.26384v1 Announce Type: new Abstract: Medical image interpretation is high-volume and time-consuming, and while AI interpretation can reduce workload, fully autonomous deployment carries pot

safetyarxiv-cs-lg

Leveraging Vision-Based Point Cloud Map Priors for Camera-Based 3D Object Detection and Online Vectorized HD Mapping

arXiv:2609.26325v1 Announce Type: cross Abstract: Camera-based 3D object detection and online vectorized HD mapping provide compact scene representations for autonomous driving, but both depend on acc

local-aiarxiv-cs-ro

Mammo-LIFE: Longitudinal Mammographic Imaging and Clinical Feature Enrichment for Post-Radiotherapy Outcome Prediction

arXiv:2609.26443v1 Announce Type: new Abstract: Recent advances in Artificial Intelligence (AI)-powered Computer-Aided Diagnosis (CAD) systems have substantially improved breast cancer screening, diag

MCPGen: Benchmarking LLMs on Executable MCPWorkflow Development

model-releasesarxiv-cs-ai

arXiv:2609.23925v1 Announce Type: cross Abstract: We study whether LLMs can produce executable workflow artifacts that remain consistent across graph structure, tool implementation, schema bindings, a

Applications

Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models

arXiv:2510.21175v2 Announce Type: replace Abstract: Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated remarkable zero-shot generalization, enabling deployment in a wide range

applicationsarxiv-cs-ai

MemoryAthena: Adaptive Routing over Latent and Generated Memories

arXiv:2609.25853v1 Announce Type: new Abstract: Learned-memory methods store information in an explicit table and consume it through a separate reader, allowing addressing, storage, and reading to be

researcharxiv-cs-cl

Neighbor-Aware Token Reduction via Hilbert Curve for Vision Transformers

arXiv:2512.22760v2 Announce Type: replace Abstract: Vision Transformers (ViTs) have achieved remarkable success in visual recognition tasks, but redundant token representations limit their computation

Optimizing Denoising Trajectories in dLLMs: A Lightweight Evolutionary Heuristic Approach

arXiv:2609.26052v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to conventional Auto-Regressive (AR) Large Language Models (LLM