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Development and Validation of a Physics-Guided Machine Learning Extrapolation Framework Using a Classical Transient Diffusion Benchmark

model-releasesarxiv-cs-lg

arXiv:2609.09912v1 Announce Type: new Abstract: Machine learning models used in engineering are typically trained within limited operating ranges, yet reliable predictions are often required beyond th

Content type

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Applications

DFNN: A Deep Frechet Neural Network Framework for Learning Metric-Space-Valued Responses

DGX agent

arXiv:2510.17072v2 Announce Type: replace-cross Abstract: Regression with non-Euclidean responses---e.g., probability distributions, networks, symmetric positive-definite matrices, and compositions---

applicationsarxiv-cs-lg

10 Sept 2026

DGCPath: Distribution-Aware Generative Contrastive Framework for Self-supervised Path Representation Learning -- Extended Version

arXiv:2609.07316v2 Announce Type: new Abstract: Due to the proliferation of vehicle trajectory data enabled by advanced sensing technologies, path representation learning has become a pivotal task in

safetyarxiv-cs-ai

DI-Bench: Systematically Generating In-Domain Data Intelligence Benchmarks for Enterprise Agents

arXiv:2609.05776v1 Announce Type: new Abstract: Evaluating enterprise agents on domain-specific benchmarks is critical, yet public benchmarks rarely evaluate whether agents can integrate business know

Agents

Diamond Agent: Agentic Control of Federated HPC Resources as a Service

arXiv:2609.06181v1 Announce Type: cross Abstract: Efficiently aggregating and orchestrating computing power across heterogeneous clusters for HPC workflows faces four practical challenges: preserving

agentsarxiv-cs-ai

Differentially Private Average Treatment Effect Estimation by Propensity Score Blocking

arXiv:2609.09536v1 Announce Type: cross Abstract: Average treatment effect (ATE) estimation in observational studies is a fundamental statistical tool used frequently in social science, medicine, and

safetyarxiv-cs-lg

Tutorials

DiffLUT-Net: Differentiable Training of FPGA LUT Networks with Learnable Connectivity

arXiv:2609.09254v1 Announce Type: new Abstract: Field-programmable gate arrays (FPGAs) enable efficient neural-network inference, but most deployment flows either accelerate multiply-accumulate operat

tutorialsarxiv-cs-lg

Diffs vs. Whole Files: An Empirical Comparison of Iterative Edit-Based and Direct Generation for Flutter/Dart Code Models

arXiv:2609.05779v1 Announce Type: cross Abstract: Large language models used for code editing can be trained and deployed in at least two output regimes: direct generation, where the model emits the e

Dimensionality Reduction for Hyperspectral Image Classification

arXiv:2609.10334v1 Announce Type: new Abstract: This paper addresses the issue of supervised classification in the context of hyperspectral satellite images. It deals with two fundamental aspects: dim

Direct Diversity Optimization for Diverse Successful Trajectories in Preference Post-Training

arXiv:2609.10052v1 Announce Type: new Abstract: LLM agents for sequential decision tasks are often post-trained with trajectory-level outcome labels, but such labels provide little supervision for pre

researcharxiv-cs-cl

DiSCo: A Distribution-First Steering and Cultural Prior Evaluation Framework for Measuring Cultural Preference Bias in LLMs

arXiv:2609.10253v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in globally used assistants, yet their default choices in culturally grounded everyday situations

local-aiarxiv-cs-cl

Distance-Aware Attention and Wall-Distance Expert Routing for Transformer-Based 3D Flow Prediction

arXiv:2609.07222v1 Announce Type: new Abstract: Transformer surrogates for 3D flow prediction compress an industrial mesh into a small set of tokens from which every prediction point reads. Two operat

researcharxiv-cs-ai

Distillation of Synthetic Data for Time Series Foundation Models

arXiv:2609.09586v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) are increasingly pre-trained on synthetically generated time series trajectories, where the data generating proc

Distilling Image Prototypes for Guided Test-Time Adaptation

arXiv:2609.09737v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) enhances the robustness of models against distribution shifts but faces two critical challenges: error accumulation from nois

Distilling Vision-Language Models for On-Device Fire Understanding

arXiv:2609.05782v1 Announce Type: new Abstract: Vision-language models (VLMs) offer a promising alternative to conventional fire detection systems by reasoning about the semantic context of a scene an

local-aiarxiv-cs-ai

Distribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts

arXiv:2609.09241v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures have emerged as a powerful paradigm for scaling model capacity while preserving efficient inference in large fo

safetyarxiv-cs-cl

Diverse Instance Generation via Diffusion Models for Enhanced Few-Shot Object Detection in Remote Sensing Images

arXiv:2511.18031v1 Announce Type: cross Abstract: Few-shot object detection (FSOD) aims to detect novel instances with only a limited number of labeled training samples, presenting a challenge that is

Do AI Coding Assistants Check Before They Install? A Pre-Registered Demand-Side Audit of Trust Signals in the Research Software Supply Chain

arXiv:2609.07754v1 Announce Type: cross Abstract: AI coding assistants now select, install, and configure software, and attackers have exploited that position through invented package names, compromis

researcharxiv-cs-ai

Do Dynamic Routers Need Memory? HeRo: History-Aware Routing for Efficient LLM Inference

arXiv:2609.08189v1 Announce Type: new Abstract: Dynamic layer routing reduces the inference cost of Large Language Models (LLMs) by learning to skip layers for individual tokens. Existing methods, how

Do Large Language Models Know What They Don't Know II? A Fully Behavioral, Non-Cognitive Measure of Epistemic Honesty

arXiv:2609.07879v1 Announce Type: new Abstract: Large Language Models (LLMs) are frequently confident, eloquent, and well versed. A natural question arises: do they know what they don't know? To answe

Do LLMs Make More Mistakes If They Do Not Believe the Input Data?

arXiv:2609.09363v1 Announce Type: new Abstract: Large language models (LLMs) are prone to hallucinating or misinterpreting facts, which impairs their usability in retrieval-augmented generation or dat

local-aiarxiv-cs-cl

Do New Attention Mechanisms Actually Fix Attention Sinks at Million-Token Context?

arXiv:2609.08574v1 Announce Type: cross Abstract: Long context language models now advertise windows of one million tokens, but two habits limit how much of that window is used. Attention heads with n

Tutorials

Do speech foundation models really learn words?

arXiv:2609.10434v1 Announce Type: new Abstract: Self-supervised speech foundation models are now used in a wide array of downstream applications, including traditional speech recognition and as the ba

tutorialsarxiv-cs-cl

Do Web Agents Investigate Before They Decide?

arXiv:2602.05354v3 Announce Type: replace Abstract: Autonomous web agents are increasingly deployed in moderation and policy enforcement, where correct decisions often depend on evidence that is not i

Does Deeper Reasoning Compromise Alignment? Revealing and Mitigating of Alignment Collapse in Large Reasoning Models

arXiv:2609.08186v1 Announce Type: new Abstract: The emergence of Chain-of-Thought (CoT) has established a robust foundation for Large Reasoning Models (LRMs). While deep reasoning is widely believed t

safetyarxiv-cs-ai

don't get distracted by all the hedging words in its name ('flash', minor version): seems like DeepSeek V4.1 Flash is a major update weights…

model-releasesclem-delangue--x

don't get distracted by all the hedging words in its name ('flash', minor version): seems like DeepSeek V4.1 Flash is a major update weights at: https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash

Applications

Dreamina Seedance 2.0 is now available to US companies on fal, hosted entirely on US infrastructure. One of the world’s most capable video m…

applicationssonya-huang--x

Dreamina Seedance 2.0 is now available to US companies on fal, hosted entirely on US infrastructure. One of the world’s most capable video models can now be deployed by US teams through fal, with infe

DSAEval: Evaluating Data Science Agents on a Wide Range of Real-World Data Science Problems

arXiv:2601.13591v3 Announce Type: replace Abstract: Recent LLM-based data agents aim to automate data science tasks ranging from data analysis to deep learning. However, the open-ended nature of real-

DUET-DINO: Simultaneous Cross-View World Modeling for Latent Planning in Robot Manipulation

arXiv:2609.10506v1 Announce Type: cross Abstract: Action-conditioned latent world models predict future visual representations, enabling zero-shot goal-conditioned robot planning and control. However,

Dynamical Non-compensatory Multidimensional IRT Model Using Variational Approximation

arXiv:2609.10028v1 Announce Type: cross Abstract: Multidimensional item response theory (MIRT) is a statistical test theory that precisely estimates multiple latent skills of learners from the respons

Dynamics of meaning: Towards the Evaluation of Diachronic Semantic Change in Sinhala

model-releasesarxiv-cs-cl

arXiv:2609.08609v2 Announce Type: replace Abstract: Tracking semantic change in low-resource languages across extensive historical timelines presents significant challenges due to data scarcity and th

EdgeMem: LLM-Free Agent Memory Construction and Retrieval via Evidence-Preserving Multi-Anchor Hypergraph

arXiv:2609.05553v1 Announce Type: new Abstract: Agent memory allows LLM agents to use earlier interactions when answering new queries. Existing methods often compress interaction histories into summar

local-aiarxiv-cs-ai

Edu-QuRating: Multi-Dimensional Educational Data Curation with Distilled Pairwise Judgements

model-releasesarxiv-cs-cl

arXiv:2609.09425v1 Announce Type: new Abstract: Educational data filters have become a practical way to improve language-model pre-training, but most filters treat educational value as a single scalar

EEGBind: Detecting Source-Level Interictal Epileptiform Discharges via EEG-Centric Multimodal Binding

model-releasesarxiv-cs-lg

arXiv:2609.09728v1 Announce Type: new Abstract: Source-level analysis of interictal epileptiform discharges (IEDs) is relevant to presurgical evaluation and treatment planning because it helps charact

Applications

Efficient Diversity-based Experience Replay for Deep Reinforcement Learning

arXiv:2410.20487v5 Announce Type: replace Abstract: Experience replay is widely used to improve learning efficiency in reinforcement learning by leveraging past experiences. However, existing experien

applicationsarxiv-cs-lg

Efficient Fairness Auditing Across Guidance Scales in Text-to-Image Diffusion Models via Causal Abstraction

arXiv:2609.09486v1 Announce Type: cross Abstract: Fairness auditing of text-to-image diffusion models often requires generating large numbers of images across sampling configurations, making comprehen

safetyarxiv-cs-cv

Efficient Graph Neural Networks for Multicarrier Wideband Hybrid Beamforming Optimization

arXiv:2609.09708v1 Announce Type: cross Abstract: 6G wireless technology is poised to adopt higher and wider frequency bands, leveraging highly directional beamforming. However, the vast bandwidths am

Efficient Leakage-Free Neural Architecture Search under Leave-One-Subject-Out Evaluation

arXiv:2609.09433v1 Announce Type: new Abstract: Leave-One-Subject-Out (LOSO) evaluation estimates generalisation performance for subject-based classification but makes Neural Architecture Search (NAS)

EFQ-Softmax: Exp-Free Quantization for Softmax

arXiv:2609.09721v1 Announce Type: new Abstract: Low-bit attention accelerates Transformer inference by moving the QK^op and PV matrix multiplications to FP8 or FP4 matrix engines. However, the softmax

local-aiarxiv-cs-lg

Agents

Elastic Horizon: Discovering the Effective Interaction Frontier in Agentic Reinforcement Learning

arXiv:2609.07247v1 Announce Type: new Abstract: Scaling the interaction horizon-the maximum number of environment interactions per episode-improves LLM agents on long-horizon tasks, and curriculum-bas

agentsarxiv-cs-ai

Elastoformer: Enabling Dynamic Adaptivity via Elastic Model Transformation

arXiv:2609.10018v1 Announce Type: new Abstract: EdgeAI systems are increasingly employing computer vision applications to enable intelligent, on-device decision-making in real-time. However, these dep

local-aiarxiv-cs-cv

Elsewise: Authoring Open-ended Interactive Narrative with Possibility Space Visualization

arXiv:2601.15295v2 Announce Type: replace-cross Abstract: Interactive narrative (IN) authors craft spaces of divergent narrative possibilities for players to explore, with the player's input determini

researcharxiv-cs-cl

EmoMed: An Emotionally-Aware Agent for Multimodal Medical Support with Real-Time Information Retrieval

arXiv:2609.07194v1 Announce Type: new Abstract: We present EmoMed - a multimodal medical consultation agent that adapts its responses based on users' emotional states while maintaining clinical accura

Encoded Early, Used Late: Where Transformers Begin to Act on an Inferred Partner's Expertise

arXiv:2609.07139v1 Announce Type: new Abstract: A transformer can make an attribute linearly decodable in its residual stream at a depth where that attribute does not yet influence the output. This ga

researcharxiv-cs-ai

Encrypt What Matters: When Selective Homomorphic Inference Is Efficient

arXiv:2609.09357v1 Announce Type: cross Abstract: Fully homomorphic encryption (FHE) enables inference on private data without revealing it to the server, but evaluating an entire input under FHE is e

local-aiarxiv-cs-lg

Enhanced Deformable Convolution with Center-invariant Offset and Edge-aware Mask

model-releasesarxiv-cs-cv

arXiv:2609.10387v1 Announce Type: new Abstract: Deformable convolution networks have recently become popular for many computer vision tasks, especially for semantic segmentation, because of their exce

Agents

EnvCraft: Synthesizing Executable Environments in Agentic RL for Claw-like Agent

arXiv:2609.05576v1 Announce Type: new Abstract: The paradigm of LLMs has rapidly shifted from passive language interfaces to autonomous Claw-like agents that execute long-horizon tasks across stateful

agentsarxiv-cs-ai

ESSA: Evolutionary Strategies for Scalable Alignment

model-releasesarxiv-cs-lg

arXiv:2507.04453v4 Announce Type: replace Abstract: Online alignment of large language models (LLMs) is dominated by reinforcement learning from human feedback (RLHF) with gradient-based optimizers su