Search: “context”

PeroMAS: A Multi-agent System of Perovskite Material Discovery

arXiv:2602.13312v2 Announce Type: replace-cross Abstract: As a pioneer of the third-generation photovoltaic revolution, Perovskite Solar Cells (PSCs) are renowned for their superior optoelectronic per

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Model Releases

Persistent Identity Preservation in Generative Image Models: A Benchmark and Evaluation System

DGX agent

arXiv:2609.04151v1 Announce Type: new Abstract: Generative image models can now produce high-quality images, follow complex instructions, and support precise edits, but they still struggle to preserve

model-releasesarxiv-cs-cv

4 Sept 2026

PL-SCEA: Reconfiguring Pretrained Attention for Few-Shot Industrial Anomaly Detection

arXiv:2609.03655v1 Announce Type: new Abstract: Vision Foundation Models (VFMs) provide transferable patch representations for few-shot industrial anomaly detection, but their attention computation is

researcharxiv-cs-cv

RARF: Region-Aware Rectified Flows for 3D Brain MRI Inpainting

arXiv:2609.03956v1 Announce Type: cross Abstract: Medical image inpainting has the potential to improve automated brain MRI analysis by reconstructing healthy tissue within pathological regions. We in

SENTINEL-RL: Offloading Topological Reasoning from LLM Agents in the Security Operations Center

arXiv:2609.04159v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly proposed as autonomous SOC analysts, but two limitations make them unreliable at enterprise scale:

Hardware

Solving the Needle-in-a-Haystack Problem in Mammography Vision-Language Model with Differentiable Subset Sampling

arXiv:2609.03085v1 Announce Type: new Abstract: There is growing interest in adopting CLIP-style vision--language model (VLM) pretraining for mammography. However, models that directly employ the stan

hardwarearxiv-cs-cv

Agents

Speak for Me: Giving LLMs the Situational Awareness to Participate in a Meeting

arXiv:2609.03923v1 Announce Type: new Abstract: In online meeting delegation, LLM agents fail to recognize when to speak. With no structured way to track stances, coverage, and floor, they miss the mo

agentsarxiv-cs-ai

The Blind Spot in 2D Infants' Pose Estimation:Robust Learning from Noisy Annotations

arXiv:2609.04009v1 Announce Type: cross Abstract: Noisy annotations pose a significant challenge for supervised deep learning, as neural networks rely on large-scale, high-quality labeled data whose c

The Impact of Synthetic Data Augmentation on Discourse-Pragmatic Function Classification

arXiv:2609.03652v1 Announce Type: new Abstract: Synthetic data augmentation has become a common strategy for addressing class imbalance in NLP, but most approaches focus on the quantity and diversity

Local Ai

The Natural Language Interaction Protocol and Standard for AI Agents

arXiv:2609.04135v1 Announce Type: new Abstract: AI agents are increasingly being developed and deployed across organizations using heterogeneous agent-development frameworks, AI models, tool interface

local-aiarxiv-cs-ai

To What Extent Do Large Language Models Understand Bangla Idioms?

arXiv:2609.03410v1 Announce Type: new Abstract: Idiomatic expressions are an integral part of natural language, reflecting cultural nuances and posing unique challenges for computational models, parti

Toward Collective-Centric Evaluation of Preference Inference for Participatory Democracy

arXiv:2609.02990v1 Announce Type: cross Abstract: To scale up collective decision-making, participatory democracy platforms such as Polis and Remesh enable online deliberation among thousands of parti

Toward Unified Robot Learning: Bridging Representation, Vision-Language-Action, and World Models

arXiv:2609.03927v1 Announce Type: new Abstract: For robots to operate reliably in real-world environments, they need to perceive their surroundings, act, and reason about the consequences of those act

safetyarxiv-cs-ro

Tree-Structured Vector Quantization For Efficient And Progressive Image Compression

arXiv:2609.03641v1 Announce Type: new Abstract: Vector-quantization based image compression has achieved strong rate--distortion performance, yet most of them still produce a separate compressed repre

researcharxiv-cs-cv

VoxPrivacy: A Benchmark for Evaluating Interactional Privacy of Speech Language Models

arXiv:2601.19956v2 Announce Type: replace-cross Abstract: As Speech Language Models (SLMs) transition from personal devices to shared, multi-user environments such as smart homes, a new challenge emer

What Else Needs Fixing? Exploring Cost-Effective Test-Time Compute for Revision Propagation in Artifacts Generated Through Conversation

arXiv:2609.03254v1 Announce Type: new Abstract: Large Language Models (LLMs) often help users generate artifacts through iterative cycles of generation and revision in conversation. A challenge here i

What Matters for Aggressive Decoding-Time KV Eviction? Temporal Aggregation and Ranking Preservation

arXiv:2609.03515v1 Announce Type: new Abstract: Decoding-time KV cache compression research focuses heavily on designing better token scoring functions, while the temporal rule that aggregates scores

WISE: World-model-guided Imagination Scheduling for Efficient Post-training of Vision-Language-Action Models

arXiv:2609.03681v1 Announce Type: new Abstract: Post-training VLA policies typically rely on supervised fine-tuning with costly expert demonstrations or reinforcement learning with expensive and poten

safetyarxiv-cs-ro

A Universal Vibe? Finding and Controlling Language-Agnostic Informal Register with SAEs

arXiv:2603.26236v2 Announce Type: replace Abstract: While multilingual language models successfully transfer factual and syntactic knowledge across languages, it remains unclear whether they process c

AffectDelta: Beyond Emotion Labels for Image Editing

arXiv:2609.02616v1 Announce Type: new Abstract: Emotion-driven image editing aims to evoke a specified target emotion by modifying emotion-relevant visual cues in a source image, while preserving the

safetyarxiv-cs-cv

Applications

Architecting Conversational Data Systems for Stateless LLM APIs: The Hydration Proxy Pattern

arXiv:2609.01834v1 Announce Type: new Abstract: As enterprise platforms transition to conversational reasoning interfaces, the stateless nature of LLM APIs creates an architectural gap. While stateles

applicationsarxiv-cs-ai

Before the Script, Set the Stage: How Worldview Simulation Amplifies Psychologically Grounded Persuasion in Multi-Turn Jailbreaking

arXiv:2609.02414v1 Announce Type: cross Abstract: Multi-turn jailbreak attacks demonstrate that harmful intent can be distributed across dialogue, yet existing methods obscure what conversational mech

Beyond Dialogue Time: Temporal Semantic Memory for Personalized LLM Agents

arXiv:2601.07468v2 Announce Type: replace Abstract: Memory enables Large Language Model (LLM) agents to perceive, store, and use information from past dialogues, which is essential for personalization

Blending Concepts: Benchmarking Visual Metaphor Generation in Text-to-Image Models

arXiv:2609.02502v1 Announce Type: cross Abstract: Text-to-image (T2I) models have achieved remarkable success at faithfully rendering specified objects and attributes, yet their ability to produce vis

C^{3}T: Counterfactual Causal Reasoning for Sentiment Shifts in Social-Media Conversation Trees

arXiv:2609.02131v1 Announce Type: cross Abstract: Sentiment in social-media threads does not only vary across posts; it shifts as users react to claims, corrections, evidence, and hostility within a b

Candidate Generation and Definition-Guided Verification for Sentence-Level Depression Symptom Recognition

arXiv:2609.01833v1 Announce Type: new Abstract: Sentence-level recognition of depression symptoms is challenging because similar expressions can differ in symptom relevance, and language-model inferen

safetyarxiv-cs-cl

CAPTURE: Disentangling Preference Drift from Memory Poisoning in Personalized LLM Agents

model-releasesarxiv-cs-lg

arXiv:2609.02265v1 Announce Type: new Abstract: Personalized language agents use persistent memory to adapt to users over time, but the same mechanism creates an attack surface. When new information c

Applications

CARPAS: Towards Content-Aware Refinement of Provided Aspects for Summarization in Large Language Models

arXiv:2510.07177v2 Announce Type: replace Abstract: Aspect-based summarization has attracted significant attention for its ability to generate more fine-grained and user-aligned summaries. While most

applicationsarxiv-cs-cl

CliffRank: A Dual-Branch Framework for Activity-Cliff Ranking Prediction

arXiv:2609.01673v1 Announce Type: cross Abstract: Activity-cliff ranking remains difficult because local structural changes can cause large activity differences, while high-quality data that resolve t

Collective creativity in hybrid societies

arXiv:2609.02620v1 Announce Type: new Abstract: Generative AI is changing how cultural artifacts are created and circulated, and with it our understanding of creativity itself. Researchers disagree ab

CORAL: An LLM-Native Harness for Production Recommender Systems

arXiv:2609.02730v1 Announce Type: new Abstract: Production recommender systems shape what billions of people see, and sustaining their performance requires continual optimization: as content, user beh

CrashDiffuser: VLM-Guided Collision Intent Reasoning for Fine-Grained Safety-Critical Traffic Scenario Generation

arXiv:2609.02270v1 Announce Type: cross Abstract: Generating safety-critical scenarios is essential for evaluating autonomous driving systems. However, existing generators primarily focus on inducing

Debias-SparseGPT: Bias-Aware Pruning for Large Language Models

arXiv:2609.02496v1 Announce Type: new Abstract: Model compression techniques such as pruning and quantization facilitate the efficient deployment and acceleration of Large Language Models (LLMs). Howe

safetyarxiv-cs-cl

Edit Knowledge, Not Just Facts via Multi-Step Reasoning over Background Stories

arXiv:2602.02028v3 Announce Type: replace Abstract: Enabling artificial intelligence systems, particularly large language models, to update knowledge and flexibly apply it during reasoning remains a c

Eliciting ESG Preferences for Reinforcement Learning-Based Portfolio Optimization

arXiv:2609.02677v1 Announce Type: cross Abstract: Modern portfolio management increasingly demands a balance between traditional risk-adjusted returns and strict Environmental, Social, and Governance

safetyarxiv-cs-lg

From Tokens to Semantics: Leveraging Complementary Signals for Hallucination Detection in Black-Box LLMs

arXiv:2609.02679v1 Announce Type: cross Abstract: When LLMs support public-facing or high-stakes workflows, missed fabrications can harm users and institutions, while false alarms consume limited huma

FUSE: An Evaluating Framework for Dangerous Capabilities of LLMs

arXiv:2609.02168v1 Announce Type: new Abstract: Fragmented safety evaluation undermines the governance of dangerous AI capabilities. We present a modular framework that evaluates each model through th

Genesis: A Generative Engine for Hierarchical Satellite Image Synthesis

model-releasesarxiv-cs-cv

arXiv:2609.02683v1 Announce Type: new Abstract: Earth observation is fundamentally multi-scale; geospatial tasks span varied resolutions, and satellite imagery is organized into cascading tile pyramid

Agents

Git4Data: Database-Native Version Control for AI Agents

arXiv:2609.02106v1 Announce Type: cross Abstract: Large Language Model (LLM) agents increasingly explore many candidate states of relational data in parallel, each of which should remain isolated, rep

agentsarxiv-cs-ai

Glass Segmentation with Fusion of Learned and General Visual Features

arXiv:2603.03718v2 Announce Type: replace Abstract: Glass surface segmentation from RGB images is a challenging task, with a number of applications in robotics and scene understanding. As glass lacks

researcharxiv-cs-cv

Local Ai

Grounded, Compute-Efficient LLM Policy Agents for Energy-Poverty Equity in Physically-Constrained Peer-to-Peer Energy Markets

arXiv:2609.01918v1 Announce Type: new Abstract: Energy poverty is nearly absent from NLP-for-social-good, and the little existing work is either static retrieval/QA or relies on carbon-intensive cloud

local-aiarxiv-cs-cl

Harness Engineering in LLM Tool Use via Agent-Native Reusable Tool Primitives

arXiv:2609.01736v1 Announce Type: cross Abstract: Large language models (LLMs) augmented with external tools have demonstrated remarkable capability in solving complex real-world tasks. However, exist

Agents

Hybrid Retrieval-Augmented Generation with Knowledge Graph Expansion, RRF Fusion, and Per-Chunk Grounded Evaluation for Enterprise Document Search

arXiv:2609.01617v1 Announce Type: cross Abstract: Getting accurate, grounded answers out of large enterprise document repositories is a difficult problem. Dense vector retrieval alone frequently perfo

agentsarxiv-cs-ai

Import What You Need: Learning When and How to Augment EHR Graphs with External Knowledge

arXiv:2609.01839v1 Announce Type: cross Abstract: Longitudinal prediction from electronic health records (EHRs) is limited by the sparsity and irregularity in patient trajectories, and knowledge augme

Large Language Models (LLMs) for Telecom Root Cause Analysis (RCA): A Structured Reasoning Framework for Evidence-Grounded Diagnosis

arXiv:2609.02805v1 Announce Type: new Abstract: Root cause analysis (RCA) is a critical task in telecom network operations, but diagnosing performance degradations in modern 5G and emerging 6G network

Learn from Whoever Is Right: Answer-Verified Multi-Teacher Distillation for Multi-Domain LLMs

arXiv:2609.02548v1 Announce Type: cross Abstract: Modern large language models (LLMs) rely on reinforcement learning to build strong capabilities in individual domains, but integrating those capabilit

Loom: Weaving Diagnostic Strands into Free-Text Consensus via Embedding-Space Reweighting

arXiv:2609.02649v1 Announce Type: new Abstract: Aggregating noisy, conflicting textual hypotheses into a reliable consensus is a fundamental challenge when deploying NLP systems in real-world industri

Applications

MISApp: Multi-Hop Intent-Aware Session Graph Learning for Next App Prediction

arXiv:2603.21653v2 Announce Type: replace Abstract: Predicting the next mobile app a user will launch is essential for proactive mobile services. Yet accurate prediction remains challenging in real-wo

applicationsarxiv-cs-lg