research

Improving Language Identification for Code-Switched Utterances with Integer Linear Programming

arXiv:2609.05099v1 Announce Type: new Abstract: Automatic identification of code-switched (CS) utterances remains a challenge for language identification (LID) systems, causing such texts to be underr

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Inductive Venn-Abers and related regressors

DGX agent

arXiv:2605.06646v2 Announce Type: replace Abstract: Venn-Abers predictors are probabilistic predictors that enjoy appealing properties of validity, but their major limitation is that they have been ap

researcharxiv-cs-lg

7 Sept 2026

Influence Score and Transformers interpretability: Measure of the Effective Impact of Attention Heads at inference time

arXiv:2609.05074v1 Announce Type: new Abstract: We propose an influence score to quantify the contribution of attention heads to classification decisions in Transformer-based models designed for promp

Interpretability for Turing Machines

arXiv:2609.04661v1 Announce Type: new Abstract: We show that susceptibilities, an interpretability technique developed for neural networks, can identify the presence of algorithmic structure in Turing

JLIR: A Julia-Native MLIR-Inspired Intermediate Representation with Automatic JACC Kernel Extraction

arXiv:2609.04585v1 Announce Type: cross Abstract: The Multi-Level Intermediate Representation (MLIR) has made reusable compiler infrastructure practical for domain-specific computation. However, MLIR'

Knowing When Not to Answer: Pseudo-Ensembles for Abstention in Music Audio-Language Models

arXiv:2609.04362v1 Announce Type: cross Abstract: Music audio-language models are evaluated almost entirely by accuracy on multiple-choice questions. This protocol forces the model to commit to an opt

Large Language Models with At Most One Spike per Neuron

arXiv:2609.05151v1 Announce Type: cross Abstract: Leveraging their inherent sparse event-driven computation, spiking neural networks (SNNs) offer a promising path toward energy-efficient large languag

Learning 3D Editing without Paired Supervision via Generative Prior Distillation

arXiv:2609.04942v1 Announce Type: new Abstract: Instruction-guided 3D editing is essential for interactive content creation, yet it faces a significant bottleneck: the severe scarcity of high-quality

Learning-Augmented Algorithms: Guarantees, Construction Mechanisms, and System-Level Implications

arXiv:2609.04787v1 Announce Type: new Abstract: Learning-augmented algorithms use fallible predictions while retaining formal performance guarantees. This survey synthesizes prediction interfaces, err

LetOccVote: Learning Weakly Supervised 3D Occupancy through Consensus

arXiv:2609.04846v1 Announce Type: new Abstract: Weakly supervised 3D occupancy prediction reduces the reliance on costly 3D annotations by learning from 2D pseudo-labels generated by vision foundation

Leveraging Low-Level Symbolic Competences for Unsupervised Grounding in Hallucination Detection

arXiv:2609.05025v1 Announce Type: cross Abstract: Hallucination-where a language model generates outputs that are factually incorrect or unsupported by the source-is a major challenge for both prompte

LookThere! Sparse Vision by Reinforced Selection

arXiv:2609.04698v1 Announce Type: new Abstract: Vision transformers typically treat every image token as equally important, yet for most tasks in computer vision only a fraction are needed. Adaptive c

Measured Sliders: Learning Continuous Controls from Differentiable Image Measurements

arXiv:2609.05234v1 Announce Type: new Abstract: Continuous sliders are useful only when coefficient changes produce predictable image changes. Yet most diffusion sliders derive their axes from text or

MedFlow: Class-Aware Multi-Scale Generation for Medical Time-Series Synthesis

arXiv:2609.04804v1 Announce Type: new Abstract: Synthetic medical time-series generation can alleviate data scarcity and support the development of reliable clinical prediction models. However, existi

Methane Detection On Board Satellites from Unorthorectified Imagery

arXiv:2609.04906v1 Announce Type: cross Abstract: As a potent greenhouse gas, methane is a major driver of climate change. Its effective mitigation relies on timely detection. Conventional detection m

MINT: A Unified Model for World-Space Camera and Hand Motion Estimation from Scalable Egocentric Pipeline Supervision

arXiv:2609.04958v1 Announce Type: new Abstract: Recovering camera and hand motion in world coordinates from egocentric video is a key capability for activity understanding, robot learning, and augment

Morphology and actuation as inductive biases in robotic hand manipulation

arXiv:2609.05206v1 Announce Type: new Abstract: Robotic hands vary widely in anatomical fidelity and mechanical complexity, and these structural choices influence the coordination of joint motions and

researcharxiv-cs-ro

Multilingual Models for Check-Worthy Social Media Posts Detection

arXiv:2408.06737v2 Announce Type: replace Abstract: This work presents an extensive study of transformer-based NLP models application for detection of social media posts that contain verifiable factua

MZ-Rain: Moisture-Budget-Guided Zero-Inflated Model for Station-Level Precipitation Nowcasting

arXiv:2609.04864v1 Announce Type: new Abstract: Accurate station-level precipitation nowcasting is critical for agriculture, water resource management, and disaster prevention, which typically is form

NEAT-POCKET: Pocket-Conditioned Autoregressive 3D Molecular Generation with a Neighborhood-Guided Set Transformer

arXiv:2609.05097v1 Announce Type: cross Abstract: AI-driven de novo molecular design offers a promising route to accelerate early-stage drug discovery by generating novel ligands directly within targe

Nepali Passport Question Answering: A Low-Resource Dataset for Public Service Applications

arXiv:2603.13320v2 Announce Type: replace-cross Abstract: Nepali, a low-resource language, faces significant challenges in building an effective information retrieval system due to the unavailability

Object Concepts Emerge from Motion

arXiv:2609.04348v1 Announce Type: new Abstract: Object-centric visual representations are important for physical-world perception, but existing visual pretraining methods often capture semantic catego

On-board ML for Trace Gas detection in Imaging Spectroscopy data

arXiv:2609.04458v1 Announce Type: new Abstract: Data collected during aerial and spaceborne imaging spectroscopy campaigns enables the detection of transient events such as trace gas emissions. Howeve

On the Abundance of Critical Points of the t-SNE Energy

arXiv:2609.04379v1 Announce Type: new Abstract: This paper considers the energy landscape of the t-SNE algorithm. While this algorithm has enjoyed broad adoption, the non-convexity of the associated e

Optimizer Memory Schedules for Outscaling the Overtraining Axis

arXiv:2609.04577v1 Announce Type: new Abstract: We investigate how optimizers scale across the overtraining axis and show that relative optimizer performance and optimal hyperparameters change substan

Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography

arXiv:2602.06761v2 Announce Type: replace-cross Abstract: Fetal echocardiography is essential for detecting congenital heart disease (CHD), facilitating pregnancy management, optimized delivery planni

Partial Inverse Design of High-Performance Concrete Using Cooperative Neural Networks for Constraint-Aware Mix Generation

arXiv:2512.06813v3 Announce Type: replace-cross Abstract: High-performance concrete (HPC) requires complex mix design decisions involving interdependent variables and practical constraints. While data

Persistent Robot World Models: Stabilizing Multi-Step Rollouts via Reinforcement Learning

arXiv:2603.25685v2 Announce Type: replace-cross Abstract: Action-conditioned robot world models generate future video frames of the manipulated scene given a robot action sequence, offering a promisin

Pitch-class Steering for Diffusion-based Music Generation via Latent-space Probes

arXiv:2609.04516v1 Announce Type: cross Abstract: Recent work on controllable music generation has focused on autoregressive models, leaving diffusion-based systems comparatively underexplored. We pre

PROMPT2BOX:Improving LLM Weakness Discovery and Specificity Estimation by Uncovering Entailment Structure among Prompts

arXiv:2603.21438v3 Announce Type: replace Abstract: To discover the weaknesses of LLMs, researchers often embed prompts into a vector space and cluster them to extract insightful patterns. However, ve

ProToMEx: Rapid, Interpretable Explanations via Structured Representations

arXiv:2609.04265v1 Announce Type: new Abstract: Existing post-hoc explainers for machine learning classifiers primarily focus on feature attribution, assigning importance scores to individual features

Proton Irradiation Characterization of an Open-Source ML Accelerator on a Zynq UltraScale+ MPSoC

arXiv:2609.05249v1 Announce Type: cross Abstract: As spaceborne computing systems increasingly rely on neural network (NN) accelerators, the opacity of commercial, black-box architectures severely res

Qlippy: A Retrieval-Augmented GenAI Assistant for Reproducible Quantum Workflows and Experiment Tracking

arXiv:2609.05039v1 Announce Type: cross Abstract: Quantum software development is iterative and error-prone. Noisy hardware and repeated re-execution make experiment tracking, provenance, and reproduc

QoNext: Towards Next-generation QoE for Foundation Models

arXiv:2509.21889v3 Announce Type: replace Abstract: Existing evaluations of foundation models predominantly focus on output correctness, treating interaction as a static exchange of information. Howev

Quality-diversity in dissimilarity spaces

arXiv:2211.12337v4 Announce Type: replace Abstract: The theory of magnitude provides a mathematical framework for quantifying and maximizing diversity. We apply this framework to formulate quality-div

ReaDiT Guidance: Control for Image and Video Generation using Diffusion Transformer Features

arXiv:2609.04649v1 Announce Type: new Abstract: We present DiT Readout (ReaDiT) Guidance, a lightweight framework for controlling generation with Diffusion Transformer (DiT) models via their internal

Recovering molecules from coarse-grained beads: free-energy-conditioned generative backmapping across chemical space

arXiv:2609.04432v1 Announce Type: cross Abstract: Transferable coarse-grained (CG) force fields compress chemical space: by aggregating atoms into a reduced set of interaction beads, models such as MA

Reducing Hallucinated Transcripts in Whisper via Hallucination Space Projection

arXiv:2609.04561v1 Announce Type: new Abstract: Whisper is a widely used foundation model for automatic speech recognition (ASR), but its generative decoder can produce fluent hallucinated transcripts

Reflection-aware Generative Novel View Synthesis

arXiv:2609.05382v1 Announce Type: cross Abstract: We propose Ref-GeNVS, a training-free, reflection-aware method for generative novel view synthesis (NVS) in mirror scenes. Existing multi-view diffusi

Regularity of Second-Order Elliptic PDEs in Spectral Barron Spaces

arXiv:2602.19381v2 Announce Type: replace-cross Abstract: We establish a regularity theorem for second-order elliptic PDEs on R^{d} in spectral Barron spaces. Under mild ellipticity and smallness assu

Repeated Queries Exhaust an LLM's Brand Recommendations but Not Its Sources

arXiv:2609.05059v1 Announce Type: cross Abstract: Whether repeated identical buying questions exhaust a language model's brand recommendations depends on retrieval. Across 300 question-engine cells (5

Representation Redundancy and Structural Complexity in Finite-Field Inversion

arXiv:2609.04583v1 Announce Type: new Abstract: The representation chosen for a mathematical operation can affect both its algebraic form and its empirical learning difficulty. We study this phenomeno

ResLearn-XR: Residual Learning for Network Traffic and Quality-of-Experience-Aware Modeling in Extended Reality

arXiv:2609.04493v1 Announce Type: new Abstract: We present ResLearn-XR, a residual learning framework for predicting eXtended Reality (XR) network traffic and estimating Quality-of-Experience (QoE) ri

Roboticists working in Learning-from-Demonstrations and Behavioral Cloning : What is going on in your field these days? [D]

researchr-machinelearning

Is LfD and BC research being effected by recent advances in (so-called) Frontier LLMs? Or is research in LfD and BC sort of going along in an independent direction from these? Are you seeing any use f

Scalable Detection of Fossil Palynomorphs in Multifocal Digital Microscopy Images

arXiv:2609.05323v1 Announce Type: new Abstract: Palynomorphs (microscopic, organic-walled fossils such as pollen, spores, and dinoflagellates) are important high-resolution records of past climates an

Scalable Neural Video Representation Compression

arXiv:2609.04273v1 Announce Type: cross Abstract: Scalable video coding (SVC) encodes a video into a layered bitstream consisting of a base layer and one or multiple enhancement layers, enabling decod

Scale-QLoRA: Code-Invariant Adapter Merging for Native 4-bit Microscaling LLMs

arXiv:2609.04526v1 Announce Type: new Abstract: Merging a LoRA adapter into its base model is standard deployment practice: it removes the runtime adapter's per-forward overhead and leaves a single st

Self-Supervised Pretraining of Molecular Graph Encoders with LeJEPA

arXiv:2609.04261v1 Announce Type: cross Abstract: Self-supervised pretraining has transformed language and vision, but its value for molecular graph neural networks remains contested. We ask whether p