Search: “framework”

When do quantum views help? Complementary classical-quantum representations in multi-view fusion

arXiv:2610.21395v1 Announce Type: cross Abstract: Recent studies have reported promising results from quantum machine learning in drug discovery, healthcare, materials science and cybersecurity. Resea

16 Oct 2026

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Agents

ABot-ER: Unified Embodied Reasoning through Agentic Data-Model Co-Evolution

DGX agent

arXiv:2610.18355v2 Announce Type: new Abstract: We introduce ABot Embodied Reasoning (ABot-ER), a unified embodied reasoning foundation model that breaks the tension between breadth and depth in embod

agentsarxiv-cs-ai

15 Oct 2026

ActMOF: Mapping Reticular Synthesis through Active Learning

model-releasesarxiv-cs-lg

arXiv:2610.19404v1 Announce Type: cross Abstract: Reticular chemistry allows metal-organic frameworks (MOFs) to be designed from their building units, yet their synthesis remains constrained by sparse

Annealed Levy Diffusion via Gaussian Surrogate Reverse Dynamics

arXiv:2610.19692v1 Announce Type: new Abstract: Gaussian diffusion models offer a practical framework for generative modeling. Denoising Levy Probabilistic Models (DLPM) introduce heavy-tailed perturb

Anticipatory Evaluation of Language Models: Predicting LLM Benchmark Scores from Descriptions

arXiv:2509.20645v4 Announce Type: replace Abstract: Modern ML research increasingly faces an evaluation bottleneck: building benchmarks and running experiments is costly, slowing iteration. We ask how

Bellman Conformal Inference: Calibrating Prediction Intervals For Time Series

arXiv:2402.05203v3 Announce Type: replace Abstract: We introduce Bellman Conformal Inference (BCI), a framework that wraps around any time series forecasting models and provides calibrated prediction

safetyarxiv-cs-lg

Beyond Corrected Actions: Training LLM Agents on Textual Critiques

arXiv:2610.19367v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for multi-turn agentic tasks that require interactions with users and environments over extended sequ

Contrastive uncertainty learning for robust multi-structure segmentation in lower-pelvic MR

arXiv:2610.20251v1 Announce Type: new Abstract: Boundary delineation of anatomical structures in prostate MRI is often compromised by regional ambiguity. Automated segmentation methods relying on glob

safetyarxiv-cs-cv

CORE: Contrast-and-Reflect for Self-Supervised Prompt Optimization in Anomaly Synthesis

arXiv:2610.19610v1 Announce Type: new Abstract: Industrial anomaly detection (AD) is bottlenecked by the scarcity of anomalous samples, making high-fidelity anomaly synthesis crucial for improving dow

researcharxiv-cs-cv

Cowork-Gym: Synthesizing Interactive Work Environments at Scale

arXiv:2610.17670v1 Announce Type: new Abstract: Cowork agents navigate dependencies across tools and files while adapting to changing user requirements and edits to shared workspaces. Scaling such env

DeltaStreamer: Towards Human-Like Agentic Streaming Video Understanding

arXiv:2610.19849v1 Announce Type: new Abstract: We propose DeltaStreamer, a novel agentic framework for streaming video understanding inspired by how humans observe, remember, and investigate. Streami

agentsarxiv-cs-cv

Dynamic Graph World Modelling: Learning Future Dynamics from Temporal Context

arXiv:2610.19364v1 Announce Type: new Abstract: Dynamic graph learning models how entities and their relations evolve from historical observations to predict future graph states. Existing methods do n

Encounter-Driven City-Scale Human Mobility Generation with Large Language Models

arXiv:2610.17672v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for human mobility generation by modeling individual routines, activities, and mobility prefere

researcharxiv-cs-ai

Tutorials

Extreme-Scale Super-Resolution of Homogeneous Turbulence from a Single Realization

arXiv:2610.20305v1 Announce Type: cross Abstract: Homogeneous turbulent flows exhibit recurring multiscale structures across spatially separated regions, suggesting that a single flow realization may

tutorialsarxiv-cs-lg

From Brewing to Resolution: Tracing the Internal Lifecycle of Code Reasoning in LLMs

arXiv:2606.17648v3 Announce Type: replace Abstract: Standard accuracy metrics cannot explain why LLMs handle variable tracking but fail on semantically equivalent loops. We study an internal lifecycle

JAL-Turn: Joint Acoustic-Linguistic Modeling for Real-Time and Robust Turn-Taking Detection in Full-Duplex Spoken Dialogue Systems

arXiv:2603.26515v2 Announce Type: replace-cross Abstract: Efficient and robust turn-taking detection remains a significant challenge in industrial-grade voice AI agents. Existing systems often rely on

KinoGen: Customizable Humanoid Loco-Manipulation References via Kinematically Grounded Video Generation

arXiv:2610.20552v1 Announce Type: new Abstract: We present KinoGen, a framework that synthesizes customizable humanoid loco-manipulation references through kinematically grounded video generation. Kin

researcharxiv-cs-ro

KiToke: Distribution-Aware Token Compression for Video Large Language Models

model-releasesarxiv-cs-cv

arXiv:2604.03414v2 Announce Type: replace Abstract: Video Large Language Models (Video LLMs) achieve strong performance on video understanding tasks but suffer from high inference costs due to the lar

Knowledge Interaction in Hypernetwork-based Continual Learning: Conflict and Composition

arXiv:2610.15677v1 Announce Type: new Abstract: Continual learning aims to adapt pretrained large language models (LLMs) to evolving data while preserving their pretrained capabilities. A central chal

Label-Centric Knowledge Retrieval for Zero-Shot Text Classification

arXiv:2610.16182v1 Announce Type: new Abstract: Flagship large language models (LLMs) offer rich general knowledge and strong reasoning capabilities, but their high inference cost and latency limit th

Large Language Model Assisted Transportation Planning through a Differentiable User Equilibrium Layer

arXiv:2610.16140v1 Announce Type: new Abstract: Transportation planning has traditionally required substantial expertise in network modeling, traffic assignment, and optimization. As a result, strateg

LATCH: LLM-Assisted Timing Closure Harness for Post-Route FPGA Optimisation

arXiv:2610.16625v1 Announce Type: new Abstract: Post-route FPGA timing closure remains expert-dependent and computationally expensive. We present LATCH (LLM-Assisted Timing Closure Harness), a two-lay

Tutorials

Learning Keypoint Constraints from Visual Demonstrations for Safe Motion Planning

arXiv:2610.19295v1 Announce Type: new Abstract: We present Keypoint Constraint Learning (KCL), a framework for learning task-relevant motion constraints from visual demonstrations and for planning saf

tutorialsarxiv-cs-ro

Learning to Select Features with Manifold Deep Unfolding PCA

model-releasesarxiv-cs-cv

arXiv:2610.19436v1 Announce Type: new Abstract: Unsupervised feature selection (UFS) is of great significance in image processing and pattern recognition. Nevertheless, existing model-based methods of

LifeSearch: Benchmarking Deep Research Agents for Real-World Life and Productivity

arXiv:2610.18092v1 Announce Type: new Abstract: Deep research (DR) agents address open-ended information needs through multi-step reasoning, long-horizon web search, and evidence synthesis. However, e

LYNX: Analytical Program Synthesis via Grounding and Closed-Loop Refinement

arXiv:2610.14777v1 Announce Type: new Abstract: LLM-powered data analytics aims to translate natural language instructions into executable analytical programs over underlying data. However, existing a

MCPDisCo: Seesaw-Mitigated Tuning for MCP-Native Agents

arXiv:2610.14956v1 Announce Type: new Abstract: The Model Context Protocol provides a shared interaction substrate for the agentic web, allowing heterogeneous services to expose capabilities through a

MolHop: Scaffold-Hopping Molecular Design with Agentic Reinforcement Learning

arXiv:2610.19920v1 Announce Type: cross Abstract: Molecular design is often formulated as an optimization problem over existing molecular spaces. However, molecular optimization and the discovery of s

Nudge the Judge: Uncovering Program Decision Hijacking in Real-World Jev Applications

arXiv:2610.18612v1 Announce Type: cross Abstract: System One models such as Jev change how software makes decisions by mapping open-ended semantic contexts into structured judgments that directly driv

One-Sided Verification Under Limited Expert Review

arXiv:2610.18089v1 Announce Type: new Abstract: AI has become increasingly helpful in scientific discovery, yet human expert review remains essential for those problems without reliable automated eval

Online Tokenization with Optimal Delay in Linear Time

arXiv:2610.19139v1 Announce Type: cross Abstract: Tokenization is an essential preprocessing step in almost all large language models (LLMs). One of the most popular frameworks is BPE tokenization, wh

Open-MMUnlearning: Unifying Methods and Evaluation for MLLM Unlearning

arXiv:2610.10358v2 Announce Type: replace Abstract: As multimodal large language models (MLLMs) become more capable and widely deployed, concerns about privacy and safety have become increasingly pres

safetyarxiv-cs-ai

Optimizing Sparse Boolean Rule Networks using Mixed Integer Linear Programming

arXiv:2610.20170v1 Announce Type: new Abstract: We study the problem of learning accurate and cognitively simple binary classifiers that are directly interpretable as Boolean rules. We propose mixed i

PLACID: Privacy-preserving Large language models for Acronym Clinical Inference and Disambiguation

arXiv:2603.23678v2 Announce Type: replace Abstract: Large Language Models (LLMs) offer transformative solutions across many domains, but healthcare integration is hindered by strict data privacy const

ProtModernBERT: Compute-Efficient Protein Language Modeling

model-releasesarxiv-cs-lg

arXiv:2610.19738v1 Announce Type: new Abstract: Large protein language models provide a powerful framework for learning sequence-function relationships and guiding experimental design. However, archit

RCR-Router: Efficient Role-Aware Context Routing for Multi-Agent LLM Systems with Structured Memory

arXiv:2508.04903v4 Announce Type: replace-cross Abstract: Large language model (LLM) agents are increasingly organized into multi-agent systems for complex reasoning and decision-making tasks. However

Recursive Environment Scaling for General Long-Horizon Agents

arXiv:2610.16397v1 Announce Type: new Abstract: We study environment scaling as a way to increase agent-benchmark difficulty while holding core task objectives fixed. Our framework, Recursive Environm

REPRO: Reflective Evolutionary Prompt Optimizer for Automated LLM Red-Teaming

arXiv:2610.15513v1 Announce Type: cross Abstract: Safety-aligned large language models (LLMs) remain vulnerable to adversarial prompts that bypass their safety training. Existing automated red-teaming

Retrieve What Helps, Only When It Helps: Agentic Reinforcement Learning for Selective Retrieval-Augmented Machine Translation

arXiv:2610.19528v1 Announce Type: new Abstract: Retrieving external knowledge can improve large language model (LLM) translation by providing supplementary information such as idiom interpretations an

agentsarxiv-cs-cl

Robust Real-Time Monocular Human Pose Estimation with Insole-Based Sensor Fusion

arXiv:2610.19494v1 Announce Type: new Abstract: Real-time monocular human pose estimation is an important sensing component for human-centered intelligent systems. While recent camera-based methods ha

researcharxiv-cs-cv

S^3-Nav: Structured Spatial-Semantic Decision Making for Language-Guided Robot Navigation

arXiv:2610.19431v1 Announce Type: new Abstract: This paper presents S^3-Nav, a structured spatial-semantic decision-making framework for language-guided robot navigation under partial observability. R

safetyarxiv-cs-ro

Scaling Personality Control in LLMs with Big Five Scaler Prompts

arXiv:2508.06149v2 Announce Type: replace Abstract: We present Big5-Scaler, a prompt-based framework for conditioning large language models (LLMs) with controllable Big Five personality traits. By emb

researcharxiv-cs-cl

SEA-HELM Audio: Evaluating Multilingual ASR-LLM Pipeline Performance Across SEA-HELM Subsets

arXiv:2610.19869v1 Announce Type: cross Abstract: We introduce SEA-HELM Audio, a Southeast Asian (SEA) multilingual evaluation framework that extends the text-based SEA-HELM benchmark to assess perfor

SMI: Ontology-Grounded Semantic IDs for Hierarchy-Aware Medical Concept Representation

arXiv:2610.18672v1 Announce Type: cross Abstract: Biomedical language models (LMs) provide strong representations for clinical tasks, but they often fail to capture the hierarchical structure among me

researcharxiv-cs-ai

SPARC: Reliable Spatial Annotations from Robot Demonstrations at Scale

model-releasesarxiv-cs-cv

arXiv:2606.13497v2 Announce Type: replace-cross Abstract: This work introduces Spatial Annotations from Robot Demonstrations with Reliability Calibration (SPARC), a risk-aware framework that automatic

Specification-Based Testing of Large Language Models

arXiv:2610.14443v1 Announce Type: cross Abstract: Model cards, system cards, and safety reports increasingly document LLM safety behaviors, yet safety evaluations typically start from predefined bench

Synthetic reaction data from transformation rules for graph-to-sequence pretraining in biodegradation pathway prediction

arXiv:2610.19640v1 Announce Type: new Abstract: The scarcity of observed biodegradation reactions constrains the training of product and pathway predictors. We present enviGraph, a framework that gene

Tutorials

Test-Time Forecasting: Recurrent Depth Enables In-Context Dynamics Prediction

arXiv:2610.19552v1 Announce Type: new Abstract: Foundation models for dynamical systems can forecast unseen partial differential equations (PDEs), ordinary differential equations (ODEs), and time seri

tutorialsarxiv-cs-lg