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CulturalMenuBench: Probing the Knowledge-Application Gap in Multimodal Culinary Reasoning

arXiv:2609.03526v1 Announce Type: new Abstract: Multimodal language models achieve near-ceiling scores on food recognition benchmarks, yet it remains unclear whether this success reflects genuine cult

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Dalek: A Constructive Agent Machine

DGX agent

arXiv:2609.03546v1 Announce Type: new Abstract: We present Dalek, a closed machine designed for agents that realizes self-maintenance, self-evolution, self-reproduction, and self-organization on any s

agentsarxiv-cs-ai

4 Sept 2026

Tutorials

Dancing with REEM-C: A robot-to-human physical-social communication study

arXiv:2408.05301v3 Announce Type: replace Abstract: Humans often work closely together and relay a wealth of information through physical interaction. Robots, on the other hand, are not yet able to wo

tutorialsarxiv-cs-ro

Data-efficient Kernel Methods for Learning Hamiltonian Systems

arXiv:2509.17154v2 Announce Type: replace-cross Abstract: Hamiltonian dynamics describe a wide range of physical systems. As such, data-driven simulations of Hamiltonian systems are important for many

Tutorials

Data Market Design through Deep Learning

arXiv:2310.20096v2 Announce Type: replace-cross Abstract: The data market design problem is a problem in economic theory to find a set of signaling schemes (statistical experiments) to maximize expect

tutorialsarxiv-cs-ai

DE-Venus: A Data-Efficient RLVR Framework for Large Language Models

arXiv:2609.03324v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves large language model reasoning, but its practical scaling is constrained by expensive on-

safetyarxiv-cs-lg

Decentralized Vision-Based Autonomous Aerial Wildlife Monitoring

arXiv:2508.15038v2 Announce Type: replace-cross Abstract: Wildlife field operations demand efficient parallel deployment methods to identify and interact with specific individuals, enabling simultaneo

Decoupled Analysis-Judging: An Automated Creativity Evaluator Using LLMs in Complex Multi-step Creativity Tasks

arXiv:2609.03432v1 Announce Type: new Abstract: Automated evaluation of creativity tasks remains challenging for LLM-as-a-Judge, as LLM is susceptible to biases such as verbosity bias and leniency bia

safetyarxiv-cs-cl

Decoupling Turn-Taking from Semantics: A Decoupled Data Approach for Finite-State-Machine-Based Full-Duplex Dialogue

arXiv:2609.03321v1 Announce Type: new Abstract: The Neural Finite State Machine (NFSM) framework offers a pragmatic path to full-duplex dialogue by serializing turn-taking control and response generat

agentsarxiv-cs-cl

Detecting Conversational Mental Manipulation with Intent-Aware Prompting

arXiv:2412.08414v2 Announce Type: replace Abstract: Mental manipulation severely undermines mental wellness by covertly and negatively distorting decision-making. While there is an increasing interest

researcharxiv-cs-cl

DIAL-GS: Dynamic Instance Aware Reconstruction for Label-free Street Scenes with 4D Gaussian Splatting

arXiv:2511.06632v2 Announce Type: replace Abstract: Urban scene reconstruction is critical for autonomous driving, enabling structured 3D representations for data synthesis and closed-loop testing. Su

agentsarxiv-cs-cv

Differentiable Hybrid Modelling for Learning and Optimising Chemical Transport Processes from Experimental Data

arXiv:2609.04011v1 Announce Type: cross Abstract: Reliable transport models are essential when modelling and optimising many chemical engineering processes, yet, most models assume hand-picked constit

safetyarxiv-cs-lg

Differentiable Interval Bottlenecks for Interpretable Anomaly Detection in Numerical Data

arXiv:2609.03878v1 Announce Type: cross Abstract: Reconstruction-based anomaly detectors are accurate but opaque: a deep autoencoder flags a sample without telling a practitioner which feature ranges

Differentially private federated learning with Byzantine-robust aggregation: A cross-domain framework for secure model training in banking and healthcare systems

arXiv:2609.03064v1 Announce Type: cross Abstract: Federated learning allows banks, hospitals, and other regulated organizations to train a shared model without moving raw records off their own servers

DisclosureBeta: A Measurement-Channel Theory for Regime-Conditioned Betas from LLM-Read Risk Disclosures

arXiv:2609.02900v1 Announce Type: cross Abstract: The problem is the beta a desk needs when a firm's price history is too short to trust: an S-1 filer, a recent listing, or a name just past a regime b

researcharxiv-cs-cl

Discovering High Level Patterns from Simulation Traces

arXiv:2602.10009v3 Announce Type: replace Abstract: Large Language Models (LLMs) are unable to reliably reason about specific physical systems. Attempts to imbue LLMs with knowledge of the necessary p

Distilled Rapid Embedding Transfer (DRET): Parameter-Efficient Biomedical Domain Adaptation via Priority-Based Embedding Transfer

model-releasesarxiv-cs-cl

arXiv:2609.02898v1 Announce Type: new Abstract: Large domain-specific language models such as BioBERT and ClinicalBERT achieve strong performance on biomedical NLP tasks, but their computational deman

Distilling deep optical flow stereo methods to retrieve dense three-dimensional wind fields

arXiv:2609.03100v1 Announce Type: new Abstract: Geostationary atmospheric motion vectors (AMVs) provide the dense horizontal wind vectors (u,v) and heights ingested into data assimilation systems. Tra

researcharxiv-cs-lg

DNative-Twin: Decision Graphs and Digital Twins for Reconstructable Agentic Decisions

arXiv:2609.03787v1 Announce Type: new Abstract: AI agents increasingly gather evidence, invoke tools, apply constraints, and produce decisions that people or software may commit to action. A final out

agentsarxiv-cs-ai

Do GUI Agents Know When Not to Act? Enabling Conflict-Aware Termination for Multimodal GUI Agents

arXiv:2609.03438v1 Announce Type: new Abstract: Graphical user interface (GUI) agents are increasingly used to execute natural-language instructions on user interfaces, yet real users may issue infeas

Do Video Generators Track the World Across Segments? A Benchmark and Method for World-State Reasoning in Video Continuation

model-releasesarxiv-cs-cv

arXiv:2609.03673v1 Announce Type: new Abstract: Video generators build long videos by composing shorter parts, either by generating segments one after another or by autoregressively extending chunks.

DogLegs: Robust Proprioceptive State Estimation for Legged Robots Using Multiple Leg-Mounted IMUs

arXiv:2503.04580v3 Announce Type: replace Abstract: Robust and accurate proprioceptive state estimation of the main body is crucial for legged robots to execute tasks in extreme environments where ext

researcharxiv-cs-ro

DRACO: Fine-Grained Credit Assignment with Dynamic Rubrics for Long-Horizon Agent Training

arXiv:2609.04094v1 Announce Type: new Abstract: Reinforcement Learning from Verifiable Rewards works well when a task has a programmatic checker, but most long-horizon agent domains have none. We work

Drive-HWM: Hierarchical World Models for Dynamic-Latent Guided Autonomous Driving

arXiv:2609.03572v1 Announce Type: new Abstract: World models offer a promising paradigm for autonomous driving by predicting how traffic scenes may evolve and using such predictions to support action

agentsarxiv-cs-cv

DropClick: Semi-Automated One-Click Segmentation for Agricultural Robotic Data

arXiv:2609.03680v1 Announce Type: new Abstract: Labelling vision datasets, especially for segmentation tasks, is a laborious and costly process that stymies novel developments in agricultural robotics

researcharxiv-cs-cv

Local Ai

DSAQuant: Denoising-Stage-Aligned Quantization-Aware Training for Video Generation

arXiv:2609.04031v1 Announce Type: new Abstract: Video diffusion models (VDMs) have achieved impressive progress in text-to-video generation, but their high memory and computational costs hinder practi

local-aiarxiv-cs-cv

DuaDeep-SeqAffinity: Dual-Branch Deep Learning for Tri-Stream Sequence-Based Antibody--Antigen Affinity Prediction

arXiv:2512.22007v2 Announce Type: replace Abstract: DuaDeep-SeqAffinity is a sequence-only deep learning framework that predicts antibody--antigen binding affinity directly from primary amino acid seq

Dual-Form ASR: Semantics-Aware Inverse Text Normalization for Chinese Speech Recognition

arXiv:2609.02901v1 Announce Type: new Abstract: Modern automatic speech recognition (ASR) scenarios require both spoken-form transcripts for faithful transcription and readable written-form transcript

researcharxiv-cs-cl

Dude: A Dual-Detection Multi-Agent System for Paper-Code Discrepancy Detection

arXiv:2609.03416v1 Announce Type: new Abstract: LLM-empowered paper-code discrepancy detection has received growing concern since the scaling of research submissions exceeds the manual review capabili

agentsarxiv-cs-ai

DuplexSpeechBench-IFEval: Evaluating Implicit Instruction Following in Full-Duplex Voice Agents

arXiv:2609.03423v1 Announce Type: new Abstract: Full-duplex voice agents must continuously decide when to listen, backchannel, interrupt, handle speech overlaps, take the floor, and yield. Existing be

EasySteer: A Unified Framework for High-Performance and Extensible LLM Steering

arXiv:2509.25175v3 Announce Type: replace-cross Abstract: Large language model (LLM) steering has emerged as a promising paradigm for controlling model behavior at inference time through targeted mani

Editable Visual Design

arXiv:2609.04034v1 Announce Type: cross Abstract: While diffusion base models such as GPT-Image-2 and Nano-Banana exhibit remarkable visual expressiveness, their end-to-end generation inherently yield

agentsarxiv-cs-cl

EF1-Constrained Nash Social Welfare with Identical Additive Valuations: Complexity, Guarantees, and Experiments

arXiv:2609.03846v1 Announce Type: cross Abstract: We study the allocation of indivisible goods among agents with identical additive valuations, focusing on envy-freeness up to one good (EF1) and Nash

safetyarxiv-cs-lg

Efficient Constant Optimization for Symbolic Regression with GPU-Accelerated Tree-Based Genetic Programming

arXiv:2609.03352v1 Announce Type: cross Abstract: Constant optimization refines the numerical coefficients of candidate expressions in tree-based genetic programming for symbolic regression. But its p

Efficient Semantic Understanding from Digital Foveation

arXiv:2609.04088v1 Announce Type: new Abstract: Dense semantic segmentation allocates computational resources uniformly across the entire image, regardless of scene complexity or task relevance. Inspi

researcharxiv-cs-cv

Efficient Test-Time Adaptation through Human-AI Interaction

arXiv:2609.04141v1 Announce Type: new Abstract: AI agents are trained on population-scale data to encode broad capabilities spanning those of many practitioners. Yet the artifacts they produce rarely

agentsarxiv-cs-ai

Hardware

EmbedTalk: Talking Head Synthesis using Gaussian Embeddings

arXiv:2603.07604v2 Announce Type: replace Abstract: Deformable 3D Gaussian Splatting (3DGS) has emerged as a popular method for real-time talking head synthesis, offering high-quality renderings at lo

hardwarearxiv-cs-cv

ENEAS: Embedding-guided Neural Ensemble for Adaptive Segmentation

arXiv:2609.03756v1 Announce Type: cross Abstract: We present ENEAS, a unified, text-promptable method for instance tracking and semantic discovery. Text-promptable segmentation models, including the l

researcharxiv-cs-ai

Enhancing Financial Question Answering: A Novel Benchmark Dataset of Banks' financial statements

arXiv:2609.03654v1 Announce Type: cross Abstract: The comparative analysis of banks' financial statements poses significant challenges for automated question answering systems due to their complexity,

Entropy-Generated Attention Beyond Softmax and Entmax: Kaniadakis and Reciprocal-Symmetric Abe Operators

arXiv:2602.08216v3 Announce Type: replace Abstract: We derive two attention operators from generalized statistical entropies. Kaniadakis entropy yields an exact full-support normalization whose weight

Environment Evolution for Terminal Agents

arXiv:2609.04128v1 Announce Type: new Abstract: Scaling interactive and verifiable environments is critical for training terminal agents. As frontier models become more capable, environments synthesiz

Tutorials

EPIC: Explicit Posterior Item Conditioning for Semantic ID Diffusion Recommendation

arXiv:2609.03522v1 Announce Type: cross Abstract: Semantic ID (SID) generative recommendation predicts the next item by generating a short tuple of discrete tokens. Recent masked-diffusion methods imp

tutorialsarxiv-cs-lg

Local Ai

Epistemic Warrant for LLM Recommendations: Characterizing the Basis for Reliance When Ground Truth Is Unavailable

arXiv:2609.04127v1 Announce Type: new Abstract: Large language models are increasingly used to support organizational decisions, yet users often lack a principled basis for assessing whether to rely o

local-aiarxiv-cs-ai

Equation Recast for Canonical Operator Learning Across Parametric PDEs

arXiv:2609.02982v1 Announce Type: new Abstract: Learning solution operators across broad parameter ranges can require substantial coverage of both input functions and physical parameters, particularly

Equilibria for Networks of Linear Translational Springs

model-releasesarxiv-cs-ro

arXiv:2609.03143v1 Announce Type: cross Abstract: We use tools from nonlinear algebra to study the equilibria of small linear translational spring networks. Specifically we use the techniques of homot

EraseSAE: Surgical Concept Erasure in Text-to-Video Diffusion Models via Sparse Autoencoders

arXiv:2609.03629v1 Announce Type: cross Abstract: Recent advances in text-to-video (T2V) diffusion models have demonstrated remarkable generative capabilities, yet their reliance on loosely curated tr

ESPO: Error-Structured Prompt Optimization via Diagnose, Diversify, and Stabilize

arXiv:2609.04197v1 Announce Type: cross Abstract: Evolutionary prompt optimizers such as GEPA suffer from prompt bloat: each iteration appends rules and caveats, producing prompts up to 3imes longer y

Establishing a Dynamic Multimodal HRI Dataset for Engagement Analysis with a Humanoid Robot

arXiv:2609.03255v1 Announce Type: new Abstract: This paper presents an experimental design for constructing a multimodal dataset to analyze user engagement in human-robot interaction (HRI). Prior stud

researcharxiv-cs-ro