Search: “persistence”

Announcing the Google Gen AI SDK for Kotlin 1.0: Idiomatic multiplatform access to Gemini

model-releasesgoogle-cloud-ai

Integrating modern generative AI capabilities into Kotlin applications shouldn't require juggling raw HTTP clients or bridging disparate Java libraries. Today, we're excited to announce the 1.0 releas

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

DGX agent

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

3 Sept 2026

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

Belief-Calibrated Optimization: An Explicit World Model for Agentic Optimization

arXiv:2609.01861v1 Announce Type: new Abstract: The performance of an LLM agent depends on the scaffold around a frozen model. A common way to improve that scaffold is to use a coding agent as an opti

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

Bilevel Coordinated Reflection: A Game-Theoretic Approach to Multi-Agent LLM Systems

arXiv:2609.02750v1 Announce Type: new Abstract: Multi-agent LLM systems commonly use an orchestrator to decompose a task for a team of workers and then improve through textual reflection. Despite stro

agentsarxiv-cs-ai

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

Convergence Theory of Knowledge Distillation in Asynchronous P2P Gossip Learning Network

arXiv:2609.01952v1 Announce Type: cross Abstract: Decentralized, serverless learning increasingly connects devices running different architectures, where the standard tool, decentralized SGD, is undef

Deeply Interleaved Text-Image Contexts for Multimodal LLMs Assessment

model-releasesarxiv-cs-cv

arXiv:2609.02573v1 Announce Type: new Abstract: Current evaluations and training of multimodal models predominantly focus on multi-image tasks, largely overlooking interleaved text-image scenarios. In

Evidence for Shared Routing Geometry and Dynamics in Sparse Mixture-of-Experts

arXiv:2609.02404v1 Announce Type: cross Abstract: Sparse mixture-of-experts (MoE) models use an independently parameterized router at each sparse layer to select experts for every token. Prior work ha

From Reweighting to Rewriting: Unlocking the Intervention Effects of Influential Samples in Training Data Attribution

arXiv:2609.02771v1 Announce Type: cross Abstract: Training data attribution (TDA) aims to identify training examples that shape model behavior, but its intervention value depends on both which example

HiPoly: a hierarchical polymer-native AI framework for property prediction and generative design

arXiv:2609.02746v1 Announce Type: cross Abstract: Polymeric materials are central to modern technologies, with applications ranging from energy to health and transportation. Although AI has made signi

ICE: Intervention-Consistent Explanation Evaluation with Statistical Grounding for LLMs

arXiv:2603.18579v2 Announce Type: replace-cross Abstract: Evaluating whether explanations faithfully reflect a model's reasoning remains an open problem. Existing benchmarks use single interventions w

On-Policy Distillation Meets Off-Policy GRPO: Training Compact Instruction-Following Rerankers

arXiv:2609.01947v1 Announce Type: cross Abstract: Compact instruction-following rerankers are attractive for deployment, but conventional distillation pipelines typically train students by offline imi

Tutorials

Oracle, will I ever learn? A study of prediction convergence and complementarity across link prediction models

arXiv:2609.02638v1 Announce Type: new Abstract: Knowledge graphs have become an important source of structured knowledge for Web applications, including search, question answering, and recommender sys

tutorialsarxiv-cs-lg

SCX Router: Streaming Zero-Shot Model Selection with a Decoder-KV Classifier and a Real-World Task Ontology

arXiv:2609.02292v1 Announce Type: new Abstract: The rapid proliferation of large language models (LLMs) and the growing diversity of their applications presents a unique optimization opportunity: sele

TempoGround: State-Aware Streaming Visual Grounding with Vision-Language Models

arXiv:2609.02359v1 Announce Type: new Abstract: Visual grounding maps language referents to spatial targets and is central to open-vocabulary perception with vision-language models. Existing methods h

TrajMind: Chaining Role-Specialized LoRAs for Fast-and-Slow Collective Trajectory Anomaly Diagnosis

arXiv:2609.02540v1 Announce Type: new Abstract: Diagnosing collective anomalies from urban trajectories is increasingly important for traffic governance, as it reveals what happened, who was involved,

researcharxiv-cs-lg

We built an open-source, model-neutral agent harness and compared it with claude managed agents - for the same model, got same accuracy, upto 75% lower cost

model-releasesr-localllama

We have been working on an open-source, model-neutral agent harness for general purpose agents called TrueForge, and wanted to understand how much the harness itself actually matters. So we ran 14 tas

What Is Worth Representing? Representational Empowerment for Continual Model Construction

arXiv:2609.02322v1 Announce Type: cross Abstract: The first problem of modeling the world is not just estimating the right parameters or causal structure, but deciding what should be represented at al

agentsarxiv-cs-ai

A Dataset for Modeling Iterative Problem-Solving

model-releasesarxiv-cs-cl

arXiv:2609.00940v1 Announce Type: new Abstract: Solving problems through repeated attempts is a sequential modeling task: at each step, the solver receives feedback and decides how to revise their sol

ASSERT: Adaptive Stochastic Sampling for Robust Diffusion Models on Analog Compute-in-Memory Hardware

arXiv:2609.00955v1 Announce Type: new Abstract: Diffusion models achieve strong image generation quality but incur high iterative denoising costs. Analog compute-in-memory (CIM) can accelerate matrix-

safetyarxiv-cs-cv

Auditing Harness Tampering in Self-Improving Agents

arXiv:2609.00069v1 Announce Type: cross Abstract: Self-improving agents iteratively modify their own harness to push the frontier of their performance. However, such modifications can produce illusory

Beneath the Diff: Diagnosing and Mitigating Algorithmic Mode Collapse in Code-Level Autonomous Research Loops

arXiv:2609.00077v1 Announce Type: new Abstract: Code-level autonomous research loops (ARLs) have recently emerged as a concrete object of study in automated machine learning research. In such loops, a

agentsarxiv-cs-cl

Beyond Blind Compliance: Benchmarking Task Verification in OCR Reasoning

model-releasesarxiv-cs-cv

arXiv:2609.00232v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved strong performance on OCR-centric document understanding and text-rich visual reasoning benchmark

Applications

Confess What You Know: Forget-Set Misalignment with Model Knowledge in LLM Unlearning

arXiv:2609.00605v1 Announce Type: cross Abstract: Machine unlearning for large language models (LLMs) often assumes that a pre-defined forget set matches what the model has memorized, but this frequen

applicationsarxiv-cs-ai

CopyShield: A Cross-Level Benchmark of Copyright Defenses in LLMs

model-releasesarxiv-cs-lg

arXiv:2609.01161v1 Announce Type: new Abstract: Large language models can reproduce memorized text verbatim, yet copyright defenses are usually evaluated under incompatible protocols. We introduce Cop

Counterfactual Fragility Certificates: Exposing High-Confidence Brittleness under Structured Evidence Failure

arXiv:2609.00366v1 Announce Type: cross Abstract: High test accuracy and good aggregate calibration do not show whether an individual prediction is structurally supported by its evidence. In tabular d

Creative Generation via Multi-Agent Debate: Does Debate Suppress Diversity?

arXiv:2609.00683v1 Announce Type: new Abstract: Creative generation tasks, such as narrative writing and scientific ideation, demand both high-quality outputs and distinct responses across independent

agentsarxiv-cs-cl

Distributed Implicit Harm: A Compositional Safety Blind Spot in MLLM-Based Video Moderation

arXiv:2609.00206v1 Announce Type: cross Abstract: Despite their growing use in video moderation, multimodal large language models (MLLMs) exhibit a compositional safety blind spot: videos composed of

Do General NLP Embeddings Capture Ontological Reasoning?

arXiv:2609.00177v1 Announce Type: cross Abstract: General-purpose NLP embedding models perform well on linguistic tasks, but their ability to capture symbolic ontological structure remains unclear. We

Evaluating Multimodal LLMs as Generalist Vision-Language-Action Agents for Drone Control: Commanding, Approaching, Tracking and Searching

arXiv:2609.01404v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are strong perceivers of images and video. We ask how far that reach extends into acting: dropping an MLLM di

EvoGS: Modeling Deformation Evolution for Dynamic Gaussian Splatting

arXiv:2609.00994v1 Announce Type: new Abstract: Recent extensions of 3D Gaussian Splatting (3DGS) enable real-time novel view synthesis in dynamic scenes by learning time-conditioned Gaussian deformat

Exploring Collaboration between a language and a non-language agent

arXiv:2609.00474v1 Announce Type: cross Abstract: LLMs are increasingly deployed as orchestrators that coordinate specialized subagents to solve complex tasks through natural language. However, in man

Finally, a good paper testing if graph memory actually beats flat retrieval for long-term agents. (bookmark this one) Researchers extract ea…

Finally, a good paper testing if graph memory actually beats flat retrieval for long-term agents. (bookmark this one) Researchers extract each conversational turn into typed nodes and attributed edges

researchdair-ai--x

Further evidence for @GaryMarcus 's worries about the security competence of the people running AI. Vibe coding without then checking securi…

Further evidence for @GaryMarcus 's worries about the security competence of the people running AI. Vibe coding without then checking security is not impressive 🚨 Attackers stole a METR API key and us

agentsgary-marcus--x

Hints Help But Do They Teach? Evaluating Skills Transfer in Code Generation

arXiv:2609.01106v1 Announce Type: cross Abstract: When a hint turns a failing generated program into a passing one, does it provide missing information or merely steer the model toward a solution it c

How Does Alignment Tuning Shape Representations of Sycophancy and Related Cue-Induced Biases in LLMs?

arXiv:2607.18114v2 Announce Type: replace-cross Abstract: Modern LLMs are alarmingly susceptible to surprisingly simple immaterial changes of input prompts: a casual hint, an incorrectly labeled few-s

Knowledge Distillation During Mid-Training Favors Reasoning over Factual Recall

arXiv:2609.01532v1 Announce Type: new Abstract: Logit-based knowledge distillation (KD) is used to train smaller language models (LMs) via supervision from stronger teachers, but whether its benefits

researcharxiv-cs-cl

Let Confidence Change, Not the Prediction: Prediction-Preserving Repair for Post-hoc Calibration

arXiv:2609.01072v1 Announce Type: cross Abstract: Post-hoc calibration corrects reported confidence, yet a multiclass calibrator can also change the associated top-1 prediction. Accuracy captures only

Mind the Rift: Cross-Scale Coupling Mismatch for AI-Generated Video Detection

arXiv:2609.00742v1 Announce Type: new Abstract: As AI video generators achieve cinematic realism, reliable detection becomes essential for safeguarding digital trust. We identify cross-scale coupling

Obstacle-Aware Autonomous Coverage and Navigation for Outdoor Robots

arXiv:2609.01384v1 Announce Type: new Abstract: Long-duration outdoor coverage with autonomous platforms remains challenging beyond classical planning: deployments face localization drift in open spac

agentsarxiv-cs-ro

Position Matters: Feature Inversion Attacks in ViT Split Inference with Token Reduction and Shuffling

arXiv:2609.01232v1 Announce Type: cross Abstract: Vision Transformers (ViTs) are increasingly used in split-inference systems, where edge devices transmit intermediate token representations to a remot

Semantic-Guided Multimodal Preprocessing for Vision Transformer-Based Clear Cell Renal Cell Carcinoma Grading

arXiv:2609.01426v1 Announce Type: cross Abstract: Clear cell renal cell carcinoma (CCRCC) grading is essential for treatment planning, yet existing approaches either analyze patch-level images directl

Some Emotions Run Deeper: Layer-wise Probing and Causal Intervention in Large Language Models

arXiv:2609.01279v1 Announce Type: cross Abstract: Emotion is expressed in text along a wide spectrum, from surface lexical cues to inferences entangled with content. Most layer-wise analyses of emotio

Applications

Teaching Vision-Language Models to Use the Scale They Are Given: Label-Free Equivariance Training for Metric Physical Reasoning

arXiv:2609.00658v1 Announce Type: new Abstract: Metric questions about video require vision-language models to use supplied real-world references to convert visual measurements into physical units. Ye

applicationsarxiv-cs-cv

The Multiple Timescales of Gradient Descent on the Edge of Stability: A Perturbative Derivation of the Central Flow

arXiv:2609.01034v1 Announce Type: new Abstract: The central flow of Cohen et al. (2025) is an empirically accurate continuous-time model of gradient descent at the edge of stability in deep learning,

researcharxiv-cs-lg

Local Ai

Topological Steering

arXiv:2609.00597v1 Announce Type: new Abstract: With the rapid rise of large language models (LLMs), controlling undesirable model behaviors has become increasingly important. Existing behavioral cont

local-aiarxiv-cs-lg