Search: “framework”

MAPLE: A Multi-Axis Parametric Knowledge Extraction Lens for LLM Evaluation

arXiv:2610.19827v1 Announce Type: cross Abstract: LLMs absorb vast knowledge from training data, yet their inherently probabilistic nature offers no guarantee that this knowledge will surface in their

researcharxiv-cs-cl

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MARS: Harmonizing Multimodal Convergence via Adaptive Rank Search

DGX agent

arXiv:2603.00720v2 Announce Type: replace Abstract: Fine-tuning Multimodal Large Language Models (MLLMs) with parameter-efficient methods like Low-Rank Adaptation (LoRA) is crucial for task adaptation

model-releasesarxiv-cs-lg

15 Oct 2026

MasalBench: A Benchmark for Contextual and Cross-Cultural Understanding of Persian Proverbs in LLMs

model-releasesarxiv-cs-cl

arXiv:2601.22050v2 Announce Type: replace Abstract: In recent years, multilingual Large Language Models (LLMs) have become an inseparable part of daily life, making it crucial for them to master the r

MCAIR: Monitoring and Correcting Agent Unfaithfulness via Internal Representations

arXiv:2610.19679v1 Announce Type: cross Abstract: Large Language Model (LLM)-based agents have demonstrated remarkable capabilities in completing complex tasks through multi-step reasoning and tool in

agentsarxiv-cs-lg

Mechanistic Knobs in LLMs: Retrieving and Steering High-Order Semantic Features via Sparse Autoencoders

arXiv:2601.02978v3 Announce Type: replace-cross Abstract: Recent work in Mechanistic Interpretability (MI) has enabled the identification and intervention of internal features in Large Language Models

applicationsarxiv-cs-ai

MedHarnessBench: A Unified Benchmark for Healthcare Agent Evaluation

model-releasesarxiv-cs-ai

arXiv:2610.15714v1 Announce Type: new Abstract: Healthcare agents must transform longitudinal clinical evidence into reliable actions through heterogeneous tools and stateful workflows, conditions und

MemDuet: Learning Dual-Process Memory for Long-Context Reasoning

arXiv:2610.19928v1 Announce Type: new Abstract: Reasoning over infinitely long documents is becoming a reality with recurrent memory agents. However, increasing context length exacerbates the trade-of

safetyarxiv-cs-cl

Tutorials

MemeLogos: Knowledge-Driven Retrieval-Augmented Reasoning for Harmful Meme Detection

arXiv:2610.15463v1 Announce Type: new Abstract: With the rapid proliferation of social media, harmful memes have become a growing threat to online ecosystems. Their harmfulness is often implicitly con

tutorialsarxiv-cs-ai

MicroSDF: Microfacet-Driven Hybrid Neural SDFs for Mixed-Reflectance Surface Reconstruction

arXiv:2610.19681v1 Announce Type: new Abstract: Accurate 3D reconstruction in real-world environments remains a significant challenge due to the coexistence of reflective and non-reflective surfaces,

applicationsarxiv-cs-cv

MIND: Instruction-Conditioned Incremental Grounding for Robots

model-releasesarxiv-cs-ro

arXiv:2610.19262v1 Announce Type: new Abstract: Robots following persistent language instructions must decide which cached room judgments remain valid as their environment changes. We present MIND (Ma

MIND: Lightweight and Effective Memory Injection Defense for LLM Agents via Intent-Aware Information Bottleneck

arXiv:2607.28103v2 Announce Type: replace Abstract: Memory-augmented LLM-based agents are vulnerable to memory injection attacks: Agents may retrieve poisoned memory from attackers, which diverts thei

agentsarxiv-cs-ai

Mitigating Video Hallucinations via Attention-Guided Representation Perturbation

model-releasesarxiv-cs-cl

arXiv:2610.19728v1 Announce Type: cross Abstract: Video large language models (Video LLMs) often generate responses unsupported by the input video. Contrastive decoding (CD) can mitigate these halluci

Mixed-Reality Feedback Control: Towards Blending of Control and Digital Twinning

arXiv:2610.19759v1 Announce Type: new Abstract: Technologies, such as co-simulation, in particular, digital twins (DTs) are used for comprehensive and reliable prototyping, verification and validation

agentsarxiv-cs-ro

Tutorials

MMKG-R1: Constructing Multimodal Knowledge Graphs via Reinforcement Learning

arXiv:2610.19341v1 Announce Type: new Abstract: Multimodal knowledge graphs (MMKGs) organize information across different modalities to support multimodal Graph Retrieval-Augmented Generation (RAG), w

tutorialsarxiv-cs-cv

Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion

arXiv:2610.20606v1 Announce Type: cross Abstract: Recent advances in robot learning have driven rapid progress in humanoid control, enabling increasingly agile behaviors in the real world. However, hu

applicationsarxiv-cs-lg

MonoMIP: Multi-Height Inverse Perspective Mapping for Monocular 3D Object Detection

arXiv:2610.19071v1 Announce Type: new Abstract: Monocular 3D object detection methods increasingly rely on depth-guided transformers, but they operate entirely in the perspective image plane where spa

researcharxiv-cs-cv

MorphAct: Robot Policies Morphing with the Worlds They Act In

model-releasesarxiv-cs-ro

arXiv:2610.20019v1 Announce Type: new Abstract: Progress toward general intelligence in the physical world requires scaling robot learning across diverse environments and interactions. However, existi

Multi-agent Undercover Gaming: Hallucination Removal via Counterfactual Test for Multimodal Reasoning

arXiv:2511.11182v2 Announce Type: replace Abstract: Hallucination continues to pose a major obstacle in the reasoning capabilities of large language models (LLMs). Although the Multi-Agent Debate (MAD

agentsarxiv-cs-ai

MultiFlow: Vision-Driven Multimodal fMRI Encoding via Stimulus-Informed Source Flow Matching

arXiv:2610.15339v1 Announce Type: new Abstract: Current fMRI encoding models frame prediction as deterministic regression, yet identical stimuli evoke a distribution of neural responses (arising from

Must-read paper from Sakana AI on orchestrating coding agents for scientific research. (bookmark it) This is an important read with lots of …

Must-read paper from Sakana AI on orchestrating coding agents for scientific research. (bookmark it) This is an important read with lots of useful insights if you are building multi-agent systems. I l

agentsdair-ai--x

Local Ai

Narrative Paradoxes in LLM Inference: Shaping Reasoning Trajectories toward Misalignment

arXiv:2610.16312v1 Announce Type: new Abstract: Explicit reasoning in large language models (LLMs) is often associated with reliability, yet it can still pose risks when a model infers harmful goals u

local-aiarxiv-cs-ai

Neos: Learning to Interleave Search and Visual Reasoning

arXiv:2610.17043v1 Announce Type: new Abstract: Recent multimodal deep search agents have advanced tool use and visual content retrieval, yet they still struggle to convert intermediate visual evidenc

safetyarxiv-cs-ai

Neural Supervised Clustering for Learning Individualized Treatment Rules with Many Treatments

arXiv:2610.19104v1 Announce Type: cross Abstract: Learning an individualized treatment rule (ITR) with many treatments requires estimating treatment-specific effects from limited observations per arm.

safetyarxiv-cs-lg

Tutorials

NeuroDETR: Multiscale Discrete Spatiotemporal Tokenization for Asynchronous EEG Event Detection

arXiv:2610.20349v1 Announce Type: new Abstract: Asynchronous EEG event detection supports practical brain-computer interfaces by identifying event classes and temporal boundaries directly from continu

tutorialsarxiv-cs-lg

New work from Meta AI on agents that manage their own search. (bookmark it) A ReAct agent keeps every failed attempt in one context, making …

New work from Meta AI on agents that manage their own search. (bookmark it) A ReAct agent keeps every failed attempt in one context, making useful evidence harder to find. To improve on this, they pro

model-releasesdair-ai--x

No Way To Steal My Face: Proactive Defense Against Identity-Preserving Personalized Generation

arXiv:2610.19717v1 Announce Type: new Abstract: Recent advances in diffusion models have enabled high-fidelity, identity-preserving image generation for personalized applications such as digital avata

researcharxiv-cs-cv

Non-asymptotic Convergence of Average-reward Q-learning with Options

arXiv:2610.20347v1 Announce Type: new Abstract: We study the finite-sample convergence of Q-learning algorithms for the average-reward formulation of Reinforcement Learning (RL) with options. While op

researcharxiv-cs-lg

NVIDIA Nemotron 3.5 Super VL Powers Specialized Agents with Multimodal Reasoning

model-releasesnvidia-developer

NVIDIA’s open‑source Nemotron 3.5 Super VL is a 120 B parameter mixture‑of‑experts multimodal model that activates only 12 B parameters per token, enabling combined reasoning, instruction following, t

ObjDream: Guiding Vision-Language-Action Models with Object-Level Understanding and Future State Prediction

arXiv:2610.20223v1 Announce Type: new Abstract: Vision-language-action (VLA) models have emerged as a powerful paradigm for robotic manipulation, enabling robots to generate actions from visual observ

applicationsarxiv-cs-ro

Of Errors and Echoes: Responsibility-Aware Credit Assignment for Tool-Use Agents

arXiv:2610.16027v1 Announce Type: cross Abstract: Reinforcement learning improves tool-use agents, yet fine-grained credit assignment remains challenging even with step-level feedback. An observed err

safetyarxiv-cs-ai

OmniPoser: Flexible Human Motion Recovery in the Wild with Masked Flow Matching

arXiv:2610.19857v1 Announce Type: new Abstract: Recovering 3D human motion from sparse wearable sensors is challenging due to the inherent noise, occlusion, and instability of real-world tracking sign

applicationsarxiv-cs-cv

On Symmetry for Characterizing Agent Heterogeneity in Multi-Agent Systems

arXiv:2610.18538v1 Announce Type: cross Abstract: Understanding agent heterogeneity can inform the design of shared and agent-specific policy representations, however existing criteria provide no unif

safetyarxiv-cs-ai

One-shot Human Video-Guided Adaptation for Vision-Language-Action Models

arXiv:2610.19746v1 Announce Type: new Abstract: Vision-language-action (VLA) models have recently achieved remarkable progress by leveraging large-scale robot datasets and foundation models for genera

safetyarxiv-cs-ro

OneLA: Learning Many Worlds from Latent Actions

arXiv:2610.20160v1 Announce Type: new Abstract: Learning world models across diverse domains calls for a unified control space, yet ac- tion interfaces vary across domains and action annotations are o

safetyarxiv-cs-cv

Local Ai

OntoAR-HAR: Ontology-Guided Agentic RAG with Personalized Memory for Human Activity Recognition

arXiv:2610.15292v1 Announce Type: new Abstract: LLMs increasingly support sensor-based human activity recognition (HAR) by linking motion signals with activity semantics and physical knowledge. Retrie

local-aiarxiv-cs-ai

OpenDepth: Repurposing Image Editing Priors for Robust Open-World Monocular Depth Estimation

arXiv:2610.17610v2 Announce Type: new Abstract: Recently, the integration of generative priors has revolutionized Monocular Depth Estimation (MDE), achieving state-of-the-art (SOTA) performance with r

Optimization for One, Feasibility for Most: Decoupling Optimization from Feasibility in Chance-Constrained Programs

model-releasesarxiv-cs-lg

arXiv:2610.19027v1 Announce Type: cross Abstract: Chance-constrained stochastic programs (CCSPs) require solutions that satisfy uncertain constraints with high probability. Standard approaches either

OT-FlowRec: Optimal Transport-Guided Multi-Bridge Flow for Multimodal Sequential Recommendation

arXiv:2610.16038v1 Announce Type: cross Abstract: E-commerce user preferences evolve dynamically within sessions, exhibiting concurrent and multi-centric interest distributions. While existing multimo

Output Discipline Sets the Floor: A Falsification-Guided, Model-Agnostic Agent Protocol for Auditable Hypothesis-Driven Decision Making

model-releasesarxiv-cs-ai

arXiv:2610.18298v1 Announce Type: new Abstract: What binds large language models on auditable, hypothesis-driven decision tasks, where every candidate can be checked against the evidence? On the publi

PACER: Process-Aware VLA Policy Learning from Human Corrections for Robotic Disassembly

model-releasesarxiv-cs-ro

arXiv:2610.19248v1 Announce Type: new Abstract: Robotic disassembly of end-of-life (EoL) products requires robots to accommodate product variation, follow prerequisite sequences, and approach componen

PatientWM: Towards Generalizable Clinical World Models via Unified Patient States

arXiv:2610.17059v1 Announce Type: new Abstract: Clinical decisions depend on anticipating how a patient's condition will evolve as treatment is adjusted and new evidence becomes available. Existing me

Hardware

PAWA: Panoramic Action-conditioned World Modeling for Multiple Agents

arXiv:2610.20240v1 Announce Type: new Abstract: A multiplayer world model must predict how the independent actions of several players change a shared environment, including changes outside a player's

hardwarearxiv-cs-cv

Phantom Merge: When Your Large Language Model Agents Pick One but Tell You About Another

arXiv:2610.16141v1 Announce Type: new Abstract: LLM agents increasingly operate over multiple entities, where reliable response generation requires not only retrieving relevant evidence but also prese

agentsarxiv-cs-ai

Physical Layer Anomaly Detection via Adaptive Gaussian Mixture Model

model-releasesarxiv-cs-lg

arXiv:2610.18946v1 Announce Type: cross Abstract: Physical-layer spoofing attacks pose a critical threat to wireless localization systems by manipulating channel state information (CSI). Detecting suc

Physics-Guided Multi-Fidelity Surrogate Modeling for Natural Supercavity Geometry of an Axisymmetric Conical Cavitator

arXiv:2610.18886v1 Announce Type: cross Abstract: Natural supercavitation behind conical cavitators generates a vapor-filled envelope that, when sustained over the full body of a high-speed underwater

researcharxiv-cs-lg

PingpongDuo: Agile Humanoid Table Tennis Doubles with Safe Team Coordination

arXiv:2610.20579v1 Announce Type: new Abstract: Unlike singles, humanoid table tennis doubles requires teammates to strike in strict alternation while sharing a confined workspace. Rapid repositioning

applicationsarxiv-cs-ro

Player-1: Learning to Play from Synthetic Experience

arXiv:2610.20584v1 Announce Type: new Abstract: Computer-use agents have demonstrated strong capabilities in interpreting screens and executing keyboard and mouse actions. However, games, with their v

agentsarxiv-cs-cv

PolyMorph: Learning Locomotion Policy for Cross-Embodiment Adaptation

arXiv:2610.19615v1 Announce Type: new Abstract: Reinforcement learning has enabled robust locomotion for legged robots, but learned policies are typically tied to a specific robot morphology and requi

safetyarxiv-cs-ro