Search: “research”

When Do Attention Circuits Form? Developmental Trajectories of Capability and Attention-Sink Emergence Across Three 1B-ClassArchitectures

arXiv:2606.02378v1 Announce Type: cross Abstract: We track the developmental trajectory of attention-head circuit formation across three 1B-class language models spanning two architecture families (de

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When Hard Negatives Hurt: Bridging the Generative-Discriminative Gap in Hard Negative Synthesis for Retrieval

DGX agent

arXiv:2606.01304v1 Announce Type: new Abstract: Hard negative mining has become the dominant strategy for training retrievers, yet it faces intrinsic limitations: negatives are bounded by corpus avail

researcharxiv-cs-lg

2 Jun 2026

When Is 0.1% Enough? Analyzing the Combined Effects of Dimensionality Reduction and Quantization on Text Embedding Compression

arXiv:2606.01074v1 Announce Type: new Abstract: Recent high-performing text embedding models often output high-dimensional real-valued vectors, resulting in substantial storage and computational costs

When Rating Scales Fall Short: LLM-Assisted Discovery of ADHD Signals in Turkish Teacher Narratives

arXiv:2606.02509v1 Announce Type: new Abstract: Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders in childhood, and its diagnosis relies on assessm

When Softmax Fails at the Top: Extreme Value Corrections for InfoNCE

arXiv:2606.00262v1 Announce Type: cross Abstract: InfoNCE is the standard contrastive learning objective, but its softmax form is not only a computational convenience: it also encodes a statistical as

Where to Refine, When to Stop: Rethinking Redundancy via Latent Discrepancy for Efficient Visual Autoregressive Generation

arXiv:2606.00310v1 Announce Type: new Abstract: Visual Autoregressive (VAR) models deliver high-quality image generation but suffer from significant inference latency at high resolutions. Recent accel

Whole-Body Inverse Kinematics with Graph Diffusion

arXiv:2606.00086v1 Announce Type: new Abstract: Inverse kinematics (IK) is a fundamental problem in robotics, requiring the generation of joint configurations that satisfy target end-effector poses. E

Why Are DMD Students Lazy? Understanding the Copying Behavior in Few-Step Distillation

arXiv:2606.02237v1 Announce Type: new Abstract: Distribution Matching Distillation (DMD) compresses pretrained diffusion models into efficient few-step generators by aligning their noised distribution

Why Do Self-Harm Prediction Models Struggle to Generalise? Lexical and Semantic Variations in Emergency Department Triage Notes

arXiv:2606.01678v1 Announce Type: new Abstract: Self-harm presentations to emergency departments (EDs) are strongly associated with higher suicide risk. NLP models have shown robust performance in det

Zero-Shot Multi-Animal Tracking in the Wild

arXiv:2511.02591v2 Announce Type: replace Abstract: Multi-animal tracking is crucial for understanding animal ecology and behavior, yet remains challenging due to variations in habitat, motion pattern

3ViewSense: Spatial and Mental Perspective Reasoning from Orthographic Views in Vision-Language Models

arXiv:2603.07751v2 Announce Type: replace-cross Abstract: Current Large Language Models have achieved Olympiad-level logic, yet Vision-Language Models paradoxically falter on elementary spatial tasks

A Context-Aware Middleware for Medical Image Based Reports: An approach based on image feature extraction and association rules

arXiv:2605.30699v1 Announce Type: cross Abstract: This work proposes a context-aware middleware for medical workflow organization and efficiency improvement. In hospitals, laboratories and teleradiolo

A holomorphic neural network framework for 3D boundary value problems governed by harmonic potentials

arXiv:2605.31231v1 Announce Type: cross Abstract: We present a neural-network-based framework for the solution of three-dimensional boundary value problems where the solution is expressible in terms o

A Novel Evaluation Metric for Unsupervised Learning in AIS-Based Maritime Anomaly Detection: MADQI

arXiv:2605.30388v1 Announce Type: new Abstract: This paper introduces a new systematic framework for detecting anomalies in maritime Automatic Identification System (AIS) datasets. These anomalies inc

A Padding Method for Enhanced Encoding of Inorganic Structures with Varying Chemical Compositions

arXiv:2605.30743v1 Announce Type: cross Abstract: Designing novel inorganic materials through generative models remains an important challenge for material science, driven by the complexity and divers

A Perturbation Approach to Unconstrained Linear Bandits

arXiv:2603.28201v2 Announce Type: replace Abstract: We revisit the standard perturbation-based approach of Abernethy et al. (2008) in the context of unconstrained Bandit Linear Optimization (uBLO). We

A Pilot Study on Curator-Guided Multilingual Art Description for Blind and Low-Vision Audiences with Small Vision-Language Models

arXiv:2605.31080v1 Announce Type: cross Abstract: Blind and low-vision (BLV) audiences remain underserved by visual art descriptions, particularly across languages and in museum settings where privacy

A Survey on Semantic Communication for Vision: Categories, Frameworks, Enabling Techniques, and Applications

arXiv:2601.22202v2 Announce Type: replace-cross Abstract: Semantic communication (SemCom) emerges as a transformative paradigm for traffic-intensive visual data transmission, shifting focus from raw d

A Unifying View of Anchoring via Operator-Side Tikhonov Regularization

arXiv:2605.30905v1 Announce Type: cross Abstract: Anchored fixed point and monotone equation methods, including Halpern iteration, extra anchored gradient, and their relatives, add a vanishing pull to

A Unifying View of Variational Generative Wasserstein Flows

arXiv:2605.31369v1 Announce Type: cross Abstract: Many modern generative models can be viewed as minimizing divergences between probability distributions, yet they rely on different algorithmic and ge

Accelerated Multiple Wasserstein Gradient Flows for Multi-objective Distributional Optimization

arXiv:2601.19220v2 Announce Type: replace Abstract: We study multi-objective optimization over probability distributions in Wasserstein space. Recently, Nguyen et al. (2025) introduced Multiple Wasser

Actuator-Aware Inverse Kinematics with Joint-Limit Admissibility for Torque-Controlled Redundant Robots

arXiv:2605.31436v1 Announce Type: new Abstract: This paper proposes actuator-aware inverse kinematics for torque-controlled redundant robots under joint-limit constraints. In the considered architectu

AdaptR1: Reinforcement Learning Based Adaptive Interleaved Thinking in Multi-hop Question Answering

arXiv:2605.31062v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable performance in complex reasoning tasks through Chain-of-Thought (CoT) prompting. However, this app

AnchorSteer: Self-Discovered Concept Injection for Structure-Preserving Music Editing

arXiv:2605.31053v1 Announce Type: cross Abstract: Controllable music editing is to modify high-level attributes while strictly preserving rhythmic and melodic structures. However, this task is challen

AR Forcing: Towards Long-Horizon Robot Navigation World Model

arXiv:2605.31314v1 Announce Type: new Abstract: The diffusion based robot navigation world models are typically trained using parallel supervision, while autoregressive inference is employed during pa

Are we chasing ghosts? Quantifying unattributable polarization, and attributing the rest to annotator groups

arXiv:2602.06055v2 Announce Type: replace Abstract: Standard agreement metrics often fail to capture systematic differences in opinion between minority and majority-group annotators, jeopardizing task

ARISTO Hand: Sensing-Driven Distal Hyperextension for Fine-Grained Manipulation

arXiv:2605.30508v1 Announce Type: new Abstract: Manipulating thin objects requires precise contact geometry and reliable force perception, yet many anthropomorphic robotic hands lack the mechanical an

Assign and Add: A Mechanistic Study of Compositional Arithmetic

arXiv:2605.31497v1 Announce Type: new Abstract: Large language models are able to compose skills in order to perform complex tasks, many of which might not have been seen during training. The details

Asymptotically Optimal Sequential Testing with Markovian Data

arXiv:2602.17587v2 Announce Type: replace-cross Abstract: We study one-sided and alpha-correct sequential hypothesis testing for data generated by an ergodic, finite-state Markov chain. The null hypot

Attention-based optimizer for symmetry finding

arXiv:2605.30429v1 Announce Type: cross Abstract: Finding symmetries is crucial for understanding physical models. In this work, we present an optimization framework that searches Pauli symmetries of

Authentication of Copy Detection Patterns via Cross-Camera Dual-Synthetic Referencing

arXiv:2605.31292v1 Announce Type: new Abstract: Copy Detection Patterns (CDPs) are structures printed on physical objects to enable cost-effective authentication. Verification is achieved by comparing

Autoregressive Visual Generation Needs a Prologue

arXiv:2605.06137v2 Announce Type: replace-cross Abstract: In this work, we propose Prologue, an approach to bridging the reconstruction-generation gap in autoregressive (AR) image generation. Instead

BackSplit: The Importance of Sub-dividing the Background in Biomedical Lesion Segmentation

arXiv:2511.19394v2 Announce Type: replace Abstract: Segmenting small lesions in medical images remains notoriously difficult. Most prior work tackles this challenge by either designing better architec

BadBone: Backdoor Attacks Against Backbone Models in Visual Prompt Learning

arXiv:2605.31246v1 Announce Type: cross Abstract: Prompt learning is a new machine learning paradigm that has attracted ample attention due to its simplicity and proven efficacy. Despite its growing a

Bayesian Inference with Shaped Deep Non-linear MLPs

arXiv:2605.30860v1 Announce Type: cross Abstract: A central aim of deep learning theory is to characterize how neural networks make predictions in the regime of simultaneously large model and training

Beyond Additive Decompositions: Interpretability Through Separability

arXiv:2605.31200v1 Announce Type: new Abstract: Interpretable machine learning requires models that are accurate and structurally faithful to the data.Existing explainability methods rely heavily on a

Beyond Tokens: Enhancing RTL Quality Estimation via Structural Graph Learning

arXiv:2508.18730v2 Announce Type: replace Abstract: Estimating the quality of register transfer level (RTL) designs is crucial in the electronic design automation (EDA) workflow, as it enables instant

Bidirectional Incremental Generalized Hybrid A*

arXiv:2605.30647v1 Announce Type: new Abstract: We focus on the problem of efficient anytime kinodynamic planning for systems with complex dynamics in unstructured environments that make precomputing

Bifurcated Remaining Useful Life Prediction: A Hybrid Approach for Realistic Uncertainty Characterization

arXiv:2605.31241v1 Announce Type: new Abstract: This study presents a novel hybrid prognostic framework for uncertainty-aware Remaining Useful Life (RUL) estimation in turbofan engines using the NASA

Bridging the Gap Between Natural Language and Market Dynamics via High-Dimensional Representation Learning

arXiv:2605.30652v1 Announce Type: new Abstract: Traditional multi-modal financial forecasting often relies on scalar sentiment scores, which fail to capture the nuances of financial news. To address t

CacheProbe: Auditing Prompt Cache Isolation in Gateway APIs

arXiv:2605.30613v1 Announce Type: cross Abstract: Over the past year, prompt caching in Large Language Models (LLMs) has become increasingly more popular across inference APIs. Prompt caching helps sa

CameraNoise: Enabling Faithful Camera Control in Video Diffusion through Geometry-Flow-Guided Noise Warping

arXiv:2605.30774v1 Announce Type: new Abstract: Precise camera pose control is critical for video diffusion, yet maintaining geometric consistency remains a challenge. Existing methods that directly i

Capturing Gaze Shifts for Guidance: Cross-Modal Fusion Enhancement for VLM Hallucination Mitigation

arXiv:2510.22067v3 Announce Type: replace Abstract: Vision language models (VLMs) often generate hallucination, i.e., content that cannot be substantiated by either textual or visual inputs. Prior wor

Certified Circuits: Stability Guarantees for Mechanistic Circuits

arXiv:2602.22968v3 Announce Type: replace Abstract: Understanding how neural networks arrive at their predictions is essential for debugging, auditing, and deployment. Mechanistic interpretability pur

Chain-of-Thought and Compressed Looped Transformers: A Memory-Budget Separation

arXiv:2605.30757v1 Announce Type: new Abstract: Chain-of-thought prompting and looped Transformers both give a fixed model more test-time computation, but they differ in what they remember. Chain-of-t

Chatterbox-Flash: Prior-Calibrated Block Diffusion for Streaming Zero-Shot TTS

arXiv:2605.30748v1 Announce Type: cross Abstract: We present Chatterbox-Flash, a zero-shot text-to-speech model obtained by fine-tuning a pretrained autoregressive TTS decoder into a block-diffusion d

Chem-PerturBridge: a harmonized compendium of small molecule perturbation transcriptomic effects

arXiv:2605.31522v1 Announce Type: new Abstract: Large perturbation models require training data encompassing chemical, cellular, and assay diversity. Current transcriptomic resources for small-molecul

Circuit-Inspired High-Order Neural Networks with Unified Neural Dynamics Modeling for PDE Solving and Visual Perception

arXiv:2603.23977v2 Announce Type: replace-cross Abstract: Deep networks often rely on architectural heuristics to shape representation evolution, limiting their ability to model data governed by intri