Search: “context”

What studies isolate back-and-forth LLM interaction from one-way sharing and self-refinement [D]

model-releasesr-machinelearning

I'm trying to find out whether back-and-forth between two different LLMs improves task success beyond strong alternatives under a controlled resource budget — and I'd rather hear that it's already set

18 Sept 2026

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Model Releases

When Perplexity Lies: Generation-Focused Distillation of Hybrid Sequence Models

DGX agent

arXiv:2603.26556v3 Announce Type: replace-cross Abstract: Converting a pretrained Transformer into a more efficient hybrid model through distillation offers a promising approach to reducing inference

model-releasesarxiv-cs-ai

18 Sept 2026

A Benchmark Suite and Ground-Truth Methodology for Formal Verification of IEC 61131-3 Ladder Diagram Programs

arXiv:2609.18994v1 Announce Type: new Abstract: We present the first benchmark suite for formal verification of Programmable Logic Controller (PLC) programs that combines controlled ground truth with

A Calibrated Instrument for Measuring How Inference Optimizations Affect Output Quality

arXiv:2609.18005v1 Announce Type: new Abstract: Large language model optimization is an active research area, spanning quantization of model weights, early-exit methods for skipping layers, and specul

ActionPiece: Rethinking Action Tokenization for Autoregressive Vision-Language-Action Models

arXiv:2609.18487v1 Announce Type: cross Abstract: Action tokenizers play a central role in autoregressive vision-language-action (VLA) models, determining both the targets for policy training and the

AdaGeoVLN: Selective Geometry Across Representation Depth and Navigation Time for Vision-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2609.18789v1 Announce Type: new Abstract: Vision-language navigation requires aligning language with visual observations while maintaining spatial understanding over time. Geometry foundation mo

Local Ai

AeroWeaver: An Embodied-Agent Harness for Weaving Aerial Skills into Distributed, Adaptive Swarm Execution

arXiv:2609.18520v1 Announce Type: new Abstract: Collective intelligence is a collaborative autonomy paradigm in which multiple agents pursue shared objectives through local perception, information exc

local-aiarxiv-cs-ai

Agora: Git as Shared Memory for Collective AutoResearch

arXiv:2609.18094v1 Announce Type: cross Abstract: Autonomous research loops such as AutoResearch show that one coding agent can improve a training setup unattended. Run several of them and each sessio

AndroidLife: Can an AI agent survive a day in the life of a real user? Qwen3.8-27b run: 56.7% SR

model-releasesr-localllama

I let AI run my phone 60 real tasks, back to back, on the OnePlus I use every day - Best text model still failed 43% of them - Peak chip temp 98.2 C - 69% of the battery gone The benchmark is AndroidL

APGEM: Adaptive Policy-Guided Error Mitigation for Quantum Reinforcement Learning on a Real-World CVRP Case Study

arXiv:2609.18219v1 Announce Type: cross Abstract: Quantum Reinforcement Learning (QRL) represents policies as variational quantum circuits (VQCs), making it attractive for combinatorial optimization s

Ask the Tool, Don't Guess: Agent Tool Calls Hold Their Progress, and the Serving System Should Read It

arXiv:2609.18849v1 Announce Type: cross Abstract: An agentic request spends substantial wall-clock time waiting for tools, and its KV cache holds GPU memory the whole time. Serving systems decide whet

Astra for Law will initially be offered to selected firms through Trusted Access in ChatGPT and Codex, with API access coming soon. We’ll ma…

Astra for Law will initially be offered to selected firms through Trusted Access in ChatGPT and Codex, with API access coming soon. We’ll maintain the legal configuration so builders can focus on thei

applicationsopenai--x

Autonomy in Check: Governor-Mediated Adaptive Security at the Edge

arXiv:2609.18338v1 Announce Type: cross Abstract: Adaptive security at the network edge increasingly relies on automated planners, including rule-based controllers, learned policies, and LLM-assisted

Behavioral Fingerprinting and Navigation Prediction in Web Browsing

arXiv:2609.18273v1 Announce Type: new Abstract: Web browsing often appears ephemeral: users visit a few websites, complete a task, and move on. However, even short fragments of browsing activity can c

researcharxiv-cs-lg

Beyond Routine Compliance: Cunning Data Cultivates Safety Vigilance in Large Language Models

arXiv:2609.18515v1 Announce Type: new Abstract: Safety alignment teaches large language models (LLMs) to recognize harmful requests and reject risky instructions. Yet aligned models can fail when harm

Can MiniMax-H3 Reason About the Physical World? An Evaluation of Omni-Modal Generative Model

arXiv:2609.18323v1 Announce Type: new Abstract: Recent Omni-Modal Generative Models (Omni-Models) have advanced content generation toward unified modeling of text, images, video, and audio. MiniMax-H3

safetyarxiv-cs-cv

Capability Emergence Can Be Forecast: Per-Seed, In Advance, With Calibrated Intervals, Certified False Alarms, and a Blind Pre-Registered Gate

arXiv:2609.19000v1 Announce Type: new Abstract: Emergent capabilities are widely treated as unpredictable: loss improves smoothly while abilities appear abruptly. Prior work offers early-warning indic

researcharxiv-cs-lg

CapMem: A Benchmark for Caption-Based Episodic Memory in Egocentric Video

arXiv:2609.17688v1 Announce Type: new Abstract: Wearable assistants require episodic memory over egocentric video, yet current vision-language models face bounded frame budgets, growing visual-token c

Claude Code + Ollama : impossible de faire fonctionner correctement les tools avec les modèles locaux

Salut, je cherche de l'aide pour un projet d'IA locale. J'ai un Dell OptiPlex 7070 Micro sous ubuntu server avec un i5-9500T, 32 Go de RAM et aucun GPU (j'en ajouterai un à l'avenir). Je sais que la m

model-releasesr-ollama

Compositional Policy Violations: When Step-Level Compliance Fails In Agentic AI Workflows

arXiv:2609.18820v1 Announce Type: new Abstract: Agentic workflows now make consequential decisions in regulated settings, and the governance placed around them is almost entirely step-scoped: input-ou

Correlation-Guided Encoder Selection for Multi-Encoder Large Audio-Language Models

arXiv:2609.18041v1 Announce Type: cross Abstract: Multi-encoder fusion extends Large Audio-Language Models (LALMs) beyond speech-centric recognition, but selecting encoders via intuition or exhaustive

CSWAM: Better Causal Semantic Representations for Out-of-Distribution Generalization in World Action Models

arXiv:2609.18462v1 Announce Type: cross Abstract: FastWAM-style world action models enable efficient action-only inference, but generalize poorly under visual distribution shifts. Their reconstruction

researcharxiv-cs-ai

Agents

Dependency-Aware Trajectory Refinement for Efficient Multi-Turn Agent Fine-Tuning

arXiv:2609.18417v1 Announce Type: new Abstract: Multi-turn agent trajectories often contain redundant rounds (failed tool calls, parallel sub-queries, verification-only steps) that inflate both traini

agentsarxiv-cs-cl

Disentangling Long-Term Memory via Latent Neuro-Symbolic Reasoning

arXiv:2609.18461v1 Announce Type: new Abstract: Personalized agents are required to reason over long-term history interactions to infer both explicit preferences and implicit behavioral evidence. Whil

researcharxiv-cs-ai

Does Moral Reasoning Training Help or Hurt? Red-Teaming RL-Trained Ethical Agents with Persona Attacks

arXiv:2609.17552v1 Announce Type: new Abstract: Moral-reward RL can make language-model agents more cooperative, but whether that alignment survives adversarial persona pressure is unknown. Such attac

DPG loss functions for learning parameter-to-solution maps by neural networks

model-releasesarxiv-cs-lg

arXiv:2506.18773v2 Announce Type: replace-cross Abstract: We develop, analyze, and experimentally explore residual-based loss functions for machine learning of parameter-to-solution maps in the contex

Enhancing knowledge tracing robustness for new question cold start in Intelligent Tutoring Systems

arXiv:2512.07179v2 Announce Type: replace Abstract: Intelligent Tutoring Systems (ITS) provide personalized learning paths by diagnosing learners' proficiency. Knowledge Tracing (KT) models play a cen

applicationsarxiv-cs-ai

EPOFusion: Exposure aware Progressive Optimization Method for Infrared and Visible Image Fusion

arXiv:2603.16130v5 Announce Type: replace Abstract: Overexposure caused by strong daylight and oncoming headlights frequently overwhelms visible sensors, resulting in critical information loss in visu

applicationsarxiv-cs-cv

Extracting Probabilistic Knowledge from Large Language Models for Bayesian Network Parameterization

arXiv:2505.15918v3 Announce Type: replace-cross Abstract: In this work, we evaluate the potential of Large Language Models (LLMs) in building Bayesian Networks (BNs) by approximating domain expert pri

applicationsarxiv-cs-ai

Fast Learning Rates for Physics-Informed Kernel Methods

arXiv:2609.18901v1 Announce Type: cross Abstract: In physics-informed machine learning, a target function u^* is learned from noisy value observations y_i=u^*(x_i)+ arepsilon_i, together with differen

researcharxiv-cs-lg

Feedback-Modulated Harmonic Policies for Quadruped Locomotion

arXiv:2609.17946v1 Announce Type: new Abstract: Learned quadruped locomotion policies commonly map observations directly to joint-level actions, leaving the periodic structure of locomotion implicit i

safetyarxiv-cs-ro

FIVE-VLA: Fast and EffectIVE Autonomous Driving with Recurrent Action Memory

model-releasesarxiv-cs-ro

arXiv:2609.18623v1 Announce Type: cross Abstract: State-of-the-art vision-language-action models (VLA) for autonomous driving face critical limitations: excessive parameter counts, inefficient high-re

ForceDelta-VLA: Distilling Force-Conditioned ActionCorrections for Contact-Rich Manipulation

arXiv:2609.18242v1 Announce Type: new Abstract: Force-aware Vision-Language-Action (VLA) policies improve contact-rich manipulation, but typically combine task-level motion and contact-dependent adjus

safetyarxiv-cs-ro

G-Mamba: Sparse Graph-Guided Mamba for Audio-Visual Speech Enhancement

arXiv:2609.18009v1 Announce Type: cross Abstract: Lightweight audio-visual speech enhancement (AVSE) models face a critical trade-off between computational efficiency and cross-modal alignment accurac

safetyarxiv-cs-cl

Gaze as Evidence for Common Grounding: A Cross-Corpus Analysis of MapTask and MUNDEX

arXiv:2609.18011v1 Announce Type: new Abstract: In collaborative tasks with asymmetric information, participants coordinate their understanding through interaction. We ask whether gaze provides eviden

researcharxiv-cs-cl

HAP: A Hand-Driven Active Perception Framework for Egocentric Head Motion Prediction

model-releasesarxiv-cs-ro

arXiv:2609.18548v1 Announce Type: cross Abstract: Egocentric motion forecasting has primarily focused on hands and manipulated objects, leaving future human head motion comparatively underexplored. Du

How Calibration Content Shapes Attention-Based Reranking

arXiv:2609.17764v1 Announce Type: new Abstract: Attention-based rerankers score documents by aggregating query-to-document attention and subtracting a null-query calibration pass to remove positional

safetyarxiv-cs-cl

Local Ai

HyQuant: Hybrid-Precision Quantization for LLM Attention

arXiv:2608.27875v3 Announce Type: replace Abstract: Quantization has been widely adopted in LLM training and inference to reduce cost and improve efficiency. However, low-bit quantization of the atten

local-aiarxiv-cs-ai

I code or AI code: A comparative evaluation of AI-rated scores in classroom observations

arXiv:2609.18274v1 Announce Type: cross Abstract: Classroom observations are widely recognized as a key tool for establishing benchmarks of education quality and guiding pedagogical improvement, yet t

Intel releases OpenVINO 2026.4

model-releasesr-localllama

UPDATE https://github.com/ggml-org/llama.cpp/pull/29009 MERGED More Gen AI coverage and frameworks integrations to minimize code changes New models supported: On CPU: Gemma-3n On CPU, GPU: Kokoro-82M,

Label-Confidence-Aware Uncertainty Estimation in Natural Language Generation

arXiv:2412.07255v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate remarkable capabilities in generative tasks but pose potential risks due to their tendency to generat

Agents

Learning Contact Dynamics through Touching: Action-conditional Graph Neural Networks for Robotic Peg Insertion

arXiv:2509.12151v3 Announce Type: replace-cross Abstract: We present a learnable physics-based model that predicts motion of the robot end effector and reaction force-torque in contact-rich manipulati

agentsarxiv-cs-lg

Learning Holistic Whole-Body Loco-Manipulation with a Bipedal Mobile Manipulator

arXiv:2609.18930v1 Announce Type: new Abstract: Bipedal loco-manipulation enables robots to interact with objects beyond the nominal workspace of their arms by coordinating locomotion and manipulation

safetyarxiv-cs-ro

Learning Where to Focus: Self-Supervised Multi-Scale ViTs for Histopathology

model-releasesarxiv-cs-cv

arXiv:2609.18578v1 Announce Type: new Abstract: Pathologists diagnose diseases by first locating suspicious tissue and then examining it at higher magnification, whereas self-supervised vision transfo

Legal LLM Hallucination Should Be Evaluated as Failure of Legal Warrant

arXiv:2609.17546v1 Announce Type: new Abstract: In this position paper, we argue that legal LLMs' hallucinations should be evaluated as a failure of legal warrant rather than as factual inaccuracy or

MINT: Multimodal Imaging-to-Speech Knowledge Transfer for Early Alzheimer's Screening

arXiv:2602.23994v2 Announce Type: replace-cross Abstract: Alzheimer's disease is a progressive neurodegenerative disorder in which mild cognitive impairment (MCI) precedes dementia. Structural MRI pro

researcharxiv-cs-ai

Agents

MIRAGE: How Conversation State Shapes Historical Evidence Use in Multimodal Personal Agents

arXiv:2609.19059v1 Announce Type: cross Abstract: Multimodal large language model (MLLM) agents are increasingly used as personal assistants for long-running tasks. Their utility depends on continuity

agentsarxiv-cs-ai

MSR: Multiple Subject Reference for Video Generation

model-releasesarxiv-cs-cv

arXiv:2609.18393v1 Announce Type: new Abstract: Conditioning a video generator on multiple images requires preserving appearance while associating each reference with its intended role. We present MSR