Search: “framework”

Cross-Protocol Personality Assessment with LLMs: Aligning Behavioral Evidence with Human Ratings

arXiv:2610.16050v1 Announce Type: new Abstract: Personality assessment from asynchronous video interviews (AVIs) plays a crucial role in recruitment by enabling standardized and behaviorally grounded

researcharxiv-cs-ai

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Model Releases

CSWBench: Evaluating Context-Sensitive Code-Switching in Creative Writing

DGX agent

arXiv:2610.20272v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated multilingual capabilities across diverse language generation and understanding tasks. Yet effective code-

model-releasesarxiv-cs-cl

15 Oct 2026

CTIA-ODE: Continuous-Time Inter-Variable Attention for Long-Term Time Series Forecasting

arXiv:2610.19831v1 Announce Type: new Abstract: Although multivariate time series forecasting has broad application prospects, effectively incorporating exogenous variables remains challenging. Prevai

safetyarxiv-cs-lg

CUSE: Fine-Grained Multimodal Unlearning with Counterfactual Guidance and On-Policy Self-Distillation

arXiv:2610.14763v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can reproduce sensitive, copyrighted, or unsafe information from their training data. Effective unlearning must

safetyarxiv-cs-ai

D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones

arXiv:2610.17124v1 Announce Type: cross Abstract: Full-duplex spoken language models (FD-SLMs) support simultaneous listening and speaking, but often lag behind half-duplex spoken language models (HD-

Data Density Scaling Laws for Image Self-Distillation

arXiv:2610.19013v1 Announce Type: new Abstract: Current scaling law formulations suggest that increasing the number of unique samples in a dataset improves model performance, while repeated exposure t

Decomposability-Guided Cooperative Coevolution for Large-Scale Itinerary Planning

arXiv:2506.06121v3 Announce Type: replace Abstract: Large-scale itinerary planning is a variant of the traveling salesman problem, aiming to determine an optimal path that maximizes the collected poin

Deep Generative Models for Phylogenetic Inference with Complex Evolutionary Processes

arXiv:2610.19053v1 Announce Type: new Abstract: Inference of phylogenetic trees from sequences plays a central role in understanding evolutionary relationships, with applications ranging from tracking

Hardware

DEEPRUBRIC: Evidence-Tree Rubric Supervision for Efficient Reinforcement Learning of Deep Research Agents

arXiv:2606.17029v2 Announce Type: replace Abstract: Deep research agents synthesize long-form reports by searching and reasoning over retrieved evidence. Reinforcement learning with rubric-based rewar

hardwarearxiv-cs-cl

Deleting Code Without Losing Knowledge: Regenerative Software for Python Libraries

arXiv:2610.17197v1 Announce Type: cross Abstract: In the age of 'Software 3.0', when a complete program can be rewritten in minutes by an agent, the traditional approach of relying on code as the sole

Depth-progressive 3D seismic velocity model building via 2D generative diffusion models

arXiv:2610.14812v1 Announce Type: cross Abstract: Three-dimensional (3D) velocity model building (VMB) remains computationally challenging with conventional approaches and native 3D neural networks, l

Diff Diffusion: Predicting Edit Paths with Diffusion Models for Efficient Code Editing

arXiv:2610.17831v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) are appealing for code generation because they can update many tokens in parallel, yet many are optimized for

local-aiarxiv-cs-ai

DiffGIPC: Differentiable Mixed-Coordinate Contact Dynamics on GPU

model-releasesarxiv-cs-ro

arXiv:2610.19091v1 Announce Type: cross Abstract: Contact-rich inverse problems require efficient gradients and reliable enforcement of non-penetration. Existing differentiable methods provide fast si

Discovering Undisclosed Concepts in LoRA Adapters for Diffusion-Based AIGC Models

arXiv:2610.18990v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) has made diffusion model personalization affordable and widely shareable, but it also creates moderation risks when harmful

local-aiarxiv-cs-lg

Discriminative Score Function: Turning Pretrained Models into Functional Generative Priors

arXiv:2610.19743v1 Announce Type: new Abstract: Discriminative models are trained with task-specific objectives such as classification, detection, or representation learning, yet their practical utili

researcharxiv-cs-cv

Tutorials

Draft-Thinking: Learning Efficient Reasoning in Long Chain-of-Thought LLMs

arXiv:2603.00578v2 Announce Type: replace-cross Abstract: Long chain-of-thought~(CoT) reasoning improves the problem-solving capability of large reasoning models~(LRMs), but often incurs substantial i

tutorialsarxiv-cs-cl

DreamHMR: From Video Generation to Human Motion Modeling via Structural Focusing

arXiv:2610.20124v1 Announce Type: new Abstract: Human mesh recovery (HMR) provides a geometric foundation for understanding human motion, but accurately reconstructing both body motion and fine hand a

local-aiarxiv-cs-cv

Driving, Fast or Slow? Neuro-Symbolic Guidance for Motion Prediction in Multi-Modal Ground Mobility

model-releasesarxiv-cs-lg

arXiv:2606.15251v2 Announce Type: replace-cross Abstract: Accurate and interpretable motion prediction for heterogeneous traffic spaces, including pedestrians, bicycles, cars, and trucks, is essential

DTDD: Divergence-Triggered Dynamic Distillation for Reliable On-Policy Supervision

arXiv:2610.19302v1 Announce Type: new Abstract: On-policy distillation (OPD) provides dense token-level supervision on student rollouts, but this supervision can become unreliable when the student and

safetyarxiv-cs-lg

DTScribe: Generating Models for Digital Twin Reporting using Local Large Language Models

arXiv:2610.18635v1 Announce Type: cross Abstract: The development of a digital twin brings together many stakeholders and technical components. We have previously investigated the reporting of the con

DuplexAct: How Interactive Are Frontier Full-Duplex Spoken Language Models?

arXiv:2610.17738v1 Announce Type: new Abstract: End-to-end (E2E) full-duplex spoken language models (FD-SLMs) enable simutanous listening and speaking continously, requiring models to take appropriate

Edgewise Envelopes Between Balanced Forman and Ollivier-Ricci Curvature

arXiv:2603.13535v5 Announce Type: cross Abstract: Evaluating Ollivier-Ricci (OR) curvature on large-scale graphs is computationally prohibitive due to the necessity of solving an optimal transport pro

Efficient contextual partial monitoring with general function approximation

arXiv:2610.19804v1 Announce Type: new Abstract: We study finite stochastic partial monitoring (PM) games with side information, a paradigm of sequential learning with partial feedback. On each round t

local-aiarxiv-cs-lg

Efficiently Learning To Reason or Not to Reason: Root-token Policy Optimization for Adaptive Thinking

arXiv:2610.17767v1 Announce Type: cross Abstract: Large reasoning models (LRMs) achieve strong performance by externalizing explicit reasoning traces before producing the answer, yet suffer from overt

local-aiarxiv-cs-ai

EGCForest: Structured Agent Memory Organization for Enterprise Group Chats

arXiv:2610.19836v1 Announce Type: new Abstract: Enterprise group chats record project progress, decisions, task ownership, and other organizational information valuable to enterprise agents. Reliable

agentsarxiv-cs-cl

Embedding Information in Policy Randomness: Distribution-Preserving Implicit Communication in MDPs

arXiv:2610.15976v1 Announce Type: cross Abstract: This paper investigates a new role of randomness in stochastic policies--as a medium for embedding and communicating information. Specifically, we con

safetyarxiv-cs-ai

EmoXpt: Analyzing Emotional Variances in Human Comments and LLM-Generated Responses

arXiv:2501.06597v1 Announce Type: cross Abstract: The widespread adoption of generative AI has generated diverse opinions, with individuals expressing both support and criticism of its applications. T

researcharxiv-cs-ai

Empirical Boundaries of Reservoir Computing for Few-Shot Sequence Pattern Tasks

arXiv:2610.19997v1 Announce Type: new Abstract: Efficient sequence modeling remains a fundamental challenge in machine learning. Despite the success of Transformers, recurrent neural networks (RNNs) h

Empowering Edge Agents: A Systematic Analysis of Edge-Cloud Collaboration in LLM Agent Execution

arXiv:2610.17816v1 Announce Type: new Abstract: Edge-cloud collaboration combines the lower inference overhead and greater data locality of edge-side execution with the stronger capabilities of cloud-

End-to-End Vision-Language-Action Policies for Autonomous Lunar Rover Docking

arXiv:2610.19224v1 Announce Type: new Abstract: Surface navigation on the Moon is subject to extreme illumination contrast and deployment-time perceptual disturbances. While modular navigation pipelin

safetyarxiv-cs-ro

Evaluating Large Language Models for Multilingual Abstractive Summarization: A Comprehensive Study of English and Bengali

model-releasesarxiv-cs-cl

arXiv:2610.19003v1 Announce Type: new Abstract: Abstractive summarization remains challenging across languages, where linguistic quality and factual consistency may diverge, particularly in low-resour

Evidence-Anchored Overdose Death Prediction from Death Investigation Reports

arXiv:2610.19556v1 Announce Type: new Abstract: Confirmation of overdose deaths in the United States is often delayed due to the complexities of certifying drug-involved deaths. Death investigation re

researcharxiv-cs-cl

Evolve Together, Fall into Place: How Social Scaffolding Shapes Self-Evolving Multi-Agent Systems

arXiv:2610.19799v1 Announce Type: new Abstract: Recent work lets LLM agents evolve their own harness, up to the team itself. Yet in human groups, the same abilities achieve different outcomes under di

agentsarxiv-cs-cl

Explorer-Zero: Improving Self-Play for Long-Horizon Tasks with Decomposable Verifiable Rewards

arXiv:2610.19868v1 Announce Type: cross Abstract: Training LLM agents on long-horizon interactive tasks with reinforcement learning typically relies on human-annotated tasks and reliable verification,

agentsarxiv-cs-lg

Exploring Interpretability in Deep Learning-Based Forest Classification - Separating Similar Forest Classes using Sentinel-2 Time Series

arXiv:2610.19270v1 Announce Type: new Abstract: The ecological insurance theory posits that diverse forests are more resilient and better able to adapt to changing environmental conditions. Increasing

F2A-ObjectNav: An Adaptive Agentic Architecture for Object-Goal Navigation

arXiv:2610.19618v1 Announce Type: new Abstract: Object-goal navigation requires an embodied agent to explore an unfamiliar environment, identify a target object, navigate toward candidate instances, a

agentsarxiv-cs-ro

FACES: Fine-grained Gated Semantic Alignment for Multimodal Emotional Support Conversation

arXiv:2610.20051v1 Announce Type: new Abstract: In recent years, with advances in multimodal interaction technologies and the growing demand for intelligent emotional support, Multimodal Emotional Sup

safetyarxiv-cs-cl

Fantastic Metrics and How to Find Them: Meta-Evaluating Metrics for Multi-lingual Style-Personalized Generation

model-releasesarxiv-cs-cl

arXiv:2610.19166v1 Announce Type: new Abstract: Meta-evaluation of text generation metrics and LLM-judges is primarily conducted using metric-human correlations. However, prior work has shown that cor

FARL: A Fully Automated Pipeline of RL Interface and Solver Design

arXiv:2610.15691v1 Announce Type: new Abstract: Existing reinforcement learning (RL) largely focuses on optimizing learning algorithms within a pre-defined task formulation, while applying RL to new t

safetyarxiv-cs-ai

FedGraph: Defending Federated Large Language Model Fine-Tuning Against Backdoor Attacks via Graph-Based Aggregation

arXiv:2610.18430v1 Announce Type: cross Abstract: Federated fine-tuning of large language models (LLMs) allows multiple clients to collaboratively adapt models without sharing raw data, offering stron

Feed-Forward Multi-View Feature Coding for 3D Gaussian Splatting

arXiv:2610.20590v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting (3DGS) methods enable efficient reconstruction of 3D scenes from sparse multi-view images in a single forward pass, w

researcharxiv-cs-cv

Applications

FleetPilot: Fine-Grained Steering Empowers Real-World LLM Personalization

arXiv:2610.14970v1 Announce Type: new Abstract: With the rapid evolution of large language models (LLMs), there is an increasing demand for effective personalization techniques that can adapt model be

applicationsarxiv-cs-ai

FlowSep-RF: Rectified Flow Matching for Single-Channel Radio-Frequency Signal Separation

arXiv:2610.20269v1 Announce Type: cross Abstract: Single-channel radio-frequency (RF) signal separation is important for interference mitigation when a signal of interest overlaps with a co-channel in

Tutorials

ForkGRPO: Efficient Exploration and Fine-Grained Credit Assignment for Diffusion Language Models

arXiv:2610.19408v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) have advanced rapidly, yet strengthening their reasoning through reinforcement learning (RL) remains an open cha

tutorialsarxiv-cs-cl

From Detection To Anticipation: Continuous Onset Forecasting For Stuttered Speech

arXiv:2610.19235v1 Announce Type: cross Abstract: Automatic stuttering systems primarily detect dysfluencies after they have occurred, limiting their use for anticipatory intervention. We address this

From Failures to Learnable Worlds: Policy-Conditioned Environment Generation for Navigation Agents

model-releasesarxiv-cs-cv

arXiv:2610.19420v1 Announce Type: cross Abstract: Simulated environments enable scalable training data generation for embodied agents, but more data does not necessarily provide what a particular agen

From Plato to Aristotle: Toward a General Theory of Representation Hypotheses

arXiv:2610.20286v1 Announce Type: new Abstract: The Platonic Representation Hypothesis (PRH) holds that increasingly capable models converge toward a common representation. However, recent studies hav

local-aiarxiv-cs-lg

From Stages to States: Unified Iterative Reasoning for MLLMs

arXiv:2610.15620v1 Announce Type: new Abstract: Multimodal Chain-of-Thought (MCoT) substantially enhances the complex reasoning capabilities of Multimodal Large Language Models (MLLMs) by explicitly m

researcharxiv-cs-ai