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arXiv:2604.10766v1 Announce Type: new Abstract: Open-set 3D macromolecule detection in cryogenic electron tomography eliminates the need for target-specific model retraining. However, strict VRAM cons

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Beyond Monologue: Interactive Talking-Listening Avatar Generation with Conversational Audio Context-Aware Kernels

DGX agent

arXiv:2604.10367v1 Announce Type: new Abstract: Audio-driven human video generation has achieved remarkable success in monologue scenarios, largely driven by advancements in powerful video generation

safetyarxiv-cs-ai

14 Apr 2026

Beyond the Beep: Scalable Collision Anticipation and Real-Time Explainability with BADAS-2.0

arXiv:2604.05767v2 Announce Type: replace-cross Abstract: We present BADAS-2.0, the second generation of our collision anticipation system, building on BADAS-1.0, which showed that fine-tuning V-JEPA2

BiT-MCTS: A Theme-based Bidirectional MCTS Approach to Chinese Fiction Generation

arXiv:2603.14410v3 Announce Type: replace Abstract: Generating long-form linear fiction from open-ended themes remains a major challenge for large language models, which frequently fail to guarantee g

researcharxiv-cs-cl

BITS Pilani at SemEval-2026 Task 9: Structured Supervised Fine-Tuning with DPO Refinement for Polarization Detection

arXiv:2604.11121v1 Announce Type: new Abstract: The POLAR SemEval-2026 Shared Task aims to detect online polarization and focuses on the classification and identification of multilingual, multicultura

BlasBench: An Open Benchmark for Irish Speech Recognition

arXiv:2604.10736v1 Announce Type: new Abstract: No open Irish-specific benchmark compares end-user ASR systems under a shared Irish-aware evaluation protocol. To solve this, we release BlasBench, an o

Both Ends Count! Just How Good are LLM Agents at 'Text-to-Big SQL'?

arXiv:2602.21480v4 Announce Type: replace-cross Abstract: Text-to-SQL and Big Data are both extensively benchmarked fields, yet there is limited research that evaluates them jointly. In the real world

Bottleneck Tokens for Unified Multimodal Retrieval

arXiv:2604.11095v1 Announce Type: cross Abstract: Adapting decoder-only multimodal large language models (MLLMs) for unified multimodal retrieval faces two structural gaps. First, existing methods rel

Catalog-Native LLM: Speaking Item-ID Dialect with Less Entanglement for Recommendation

arXiv:2510.05125v2 Announce Type: replace Abstract: While collaborative filtering delivers predictive accuracy and efficiency, and Large Language Models (LLMs) enable expressive and generalizable reas

researcharxiv-cs-cl

CocoaBench: Evaluating Unified Digital Agents in the Wild

arXiv:2604.11201v1 Announce Type: cross Abstract: LLM agents now perform strongly in software engineering, deep research, GUI automation, and various other applications, while recent agent scaffolds a

CoFusion: Multispectral and Hyperspectral Image Fusion via Spectral Coordinate Attention

arXiv:2604.10584v1 Announce Type: new Abstract: Multispectral and Hyperspectral Image Fusion (MHIF) aims to reconstruct high-resolution images by integrating low-resolution hyperspectral images (LRHSI

COMPOSITE-Stem

arXiv:2604.09836v1 Announce Type: new Abstract: AI agents hold growing promise for accelerating scientific discovery; yet, a lack of frontier evaluations hinders adoption into real workflows. Expert-w

Context-Aware Semantic Segmentation via Stage-Wise Attention

arXiv:2601.11310v2 Announce Type: replace Abstract: Semantic ultra-high-resolution (UHR) image segmentation is essential in remote sensing applications such as aerial mapping and environmental monitor

Agents

Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training

arXiv:2507.15640v2 Announce Type: replace-cross Abstract: Continual pre-training on small-scale task-specific data is an effective method for improving large language models in new target fields, yet

agentsarxiv-cs-ai

DDO-RM for LLM Preference Optimization: A Minimal Held-Out Benchmark against DPO

model-releasesarxiv-cs-lg

arXiv:2604.11119v1 Announce Type: cross Abstract: This paper reorganizes the current manuscript around the DPO versus DDO-RM preference-optimization project and focuses on two parts: the algorithmic v

DeepSketcher: Internalizing Visual Manipulation for Multimodal Reasoning

arXiv:2509.25866v2 Announce Type: replace Abstract: The 'thinking with images' paradigm represents a pivotal shift in the reasoning of Vision Language Models (VLMs), moving from text-dominant chain-of

researcharxiv-cs-cv

Differentially Private Verification of Distribution Properties

model-releasesarxiv-cs-lg

arXiv:2604.10819v1 Announce Type: cross Abstract: A recent line of work initiated by Chiesa and Gur and further developed by Herman and Rothblum investigates the sample and communication complexity of

Diffusion-Based Generative Priors for Efficient Beam Alignment in Directional Networks

arXiv:2604.09653v1 Announce Type: cross Abstract: Beam alignment is a key challenge in directional mmWave and THz systems, where narrow beams require accurate yet low-overhead training. Existing learn

Diffusion-CAM: Faithful Visual Explanations for dMLLMs

arXiv:2604.11005v1 Announce Type: new Abstract: While diffusion Multimodal Large Language Models (dMLLMs) have recently achieved remarkable strides in multimodal generation, the development of interpr

Discourse Diversity in Multi-Turn Empathic Dialogue

arXiv:2604.11742v1 Announce Type: cross Abstract: Large language models (LLMs) produce responses rated as highly empathic in single-turn settings (Ayers et al., 2023; Lee et al., 2024), yet they are a

Do LLMs Know Tool Irrelevance? Demystifying Structural Alignment Bias in Tool Invocations

arXiv:2604.11322v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated impressive capabilities in utilizing external tools. In practice, however, LLMs are often exposed to to

Applications

EDUMATH: Generating Standards-aligned Educational Math Word Problems

arXiv:2510.06965v2 Announce Type: replace-cross Abstract: Math word problems (MWPs) are critical K-12 educational tools, and customizing them to students' interests and ability levels can enhance lear

applicationsarxiv-cs-ai

Endogenous Information in Routing Games: Memory-Constrained Equilibria, Recall Braess Paradoxes, and Memory Design

arXiv:2604.11733v1 Announce Type: cross Abstract: We study routing games in which travelers optimize over routes that are remembered or surfaced, rather than over a fixed exogenous action set. The pap

Tutorials

Engineering Resource-constrained Software Systems with DNN Components: a Concept-based Pruning Approach

arXiv:2604.09988v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) are widely used by engineers to solve difficult problems that require predictive modeling from data. However, these models

tutorialsarxiv-cs-lg

EviRCOD: Evidence-Guided Probabilistic Decoding for Referring Camouflaged Object Detection

arXiv:2604.10894v1 Announce Type: new Abstract: Referring Camouflaged Object Detection (Ref-COD) focuses on segmenting specific camouflaged targets in a query image using category-aligned references.

EvoESAP: Non-Uniform Expert Pruning for Sparse MoE

arXiv:2603.06003v2 Announce Type: replace Abstract: Sparse Mixture-of-Experts (SMoE) language models achieve strong capability at low per-token compute, yet deployment remains constrained by memory fo

researcharxiv-cs-lg

Exploring Cross-Modal Flows for Few-Shot Learning

arXiv:2510.14543v4 Announce Type: replace Abstract: Aligning features from different modalities, is one of the most fundamental challenges for cross-modal tasks. Although pre-trained vision-language m

Exploring the best way for UAV visual localization under Low-altitude Multi-view Observation Condition: a Benchmark

arXiv:2503.10692v2 Announce Type: replace Abstract: Absolute Visual Localization (AVL) enables an Unmanned Aerial Vehicle (UAV) to determine its position in GNSS-denied environments by establishing ge

Face Density as a Proxy for Data Complexity: Quantifying the Hardness of Instance Count

arXiv:2604.09689v1 Announce Type: cross Abstract: Machine learning progress has historically prioritized model-centric innovations, yet achievable performance is frequently capped by the intrinsic com

FACT-E: Causality-Inspired Evaluation for Trustworthy Chain-of-Thought Reasoning

arXiv:2604.10693v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting has improved LLM reasoning, but models often generate explanations that appear coherent while containing unfaithful int

FAITH: Factuality Alignment through Integrating Trustworthiness and Honestness

arXiv:2604.10189v1 Announce Type: new Abstract: Large Language Models (LLMs) can generate factually inaccurate content even if they have corresponding knowledge, which critically undermines their reli

safetyarxiv-cs-cl

From Perception to Planning: Evolving Ego-Centric Task-Oriented Spatiotemporal Reasoning via Curriculum Learning

arXiv:2604.10517v1 Announce Type: new Abstract: Modern vision-language models achieve strong performance in static perception, but remain limited in the complex spatiotemporal reasoning required for e

GanitLLM: Difficulty-Aware Bengali Mathematical Reasoning through Curriculum-GRPO

arXiv:2601.06767v2 Announce Type: replace-cross Abstract: We present a Bengali mathematical reasoning model called GanitLLM (named after the Bangla word for mathematics, 'Ganit'), together with a new

GazeVaLM: A Multi-Observer Eye-Tracking Benchmark for Evaluating Clinical Realism in AI-Generated X-Rays

arXiv:2604.11653v1 Announce Type: new Abstract: We introduce GazeVaLM, a public eye-tracking dataset for studying clinical perception during chest radiograph authenticity assessment. The dataset compr

GenProve: Learning to Generate Text with Fine-Grained Provenance

arXiv:2601.04932v2 Announce Type: replace Abstract: Large language models (LLM) often hallucinate, and while adding citations is a common solution, it is frequently insufficient for accountability as

safetyarxiv-cs-cl

Governed Reasoning for Institutional AI

arXiv:2604.10658v1 Announce Type: new Abstract: Institutional decisions -- regulatory compliance, clinical triage, prior authorization appeal -- require a different AI architecture than general-purpos

HeceTokenizer: A Syllable-Based Tokenization Approach for Turkish Retrieval

arXiv:2604.10665v1 Announce Type: new Abstract: HeceTokenizer is a syllable-based tokenizer for Turkish that exploits the deterministic six-pattern phonological structure of the language to construct

How LLMs Might Think

arXiv:2604.09674v1 Announce Type: new Abstract: Do large language models (LLMs) think? Daniel Stoljar and Zhihe Vincent Zhang have recently developed an argument from rationality for the claim that LL

How You Ask Matters! Adaptive RAG Robustness to Query Variations

arXiv:2604.10745v1 Announce Type: new Abstract: Adaptive Retrieval-Augmented Generation (RAG) promises accuracy and efficiency by dynamically triggering retrieval only when needed and is widely used i

I Can't Believe TTA Is Not Better: When Test-Time Augmentation Hurts Medical Image Classification

arXiv:2604.09697v1 Announce Type: cross Abstract: Test-time augmentation (TTA)--aggregating predictions over multiple augmented copies of a test input--is widely assumed to improve classification accu

I Walk the Line: Examining the Role of Gestalt Continuity in Object Binding for Vision Transformers

arXiv:2604.09942v1 Announce Type: cross Abstract: Object binding is a foundational process in visual cognition, during which low-level perceptual features are joined into object representations. Bindi

IMPACT: A Dataset for Multi-Granularity Human Procedural Action Understanding in Industrial Assembly

arXiv:2604.10409v1 Announce Type: cross Abstract: We introduce IMPACT, a synchronized five-view RGB-D dataset for deployment-oriented industrial procedural understanding, built around real assembly an

Improving understanding and trust in AI: How users benefit from interval-based counterfactual explanations

arXiv:2604.09573v1 Announce Type: cross Abstract: Experimental user studies evaluating the effectiveness of different subtypes of post-hoc explanations for black-box models are largely nonexistent. Th

researcharxiv-cs-lg

Local Ai

Inertial Magnetic SLAM Systems Using Low-Cost Sensors

arXiv:2512.10128v2 Announce Type: replace Abstract: Spatially inhomogeneous magnetic fields offer a valuable, non-visual information source for positioning. Among systems leveraging this, magnetic fie

local-aiarxiv-cs-ro

Investigating Bias and Fairness in Appearance-based Gaze Estimation

arXiv:2604.10707v1 Announce Type: new Abstract: While appearance-based gaze estimation has achieved significant improvements in accuracy and domain adaptation, the fairness of these systems across dif

Tutorials

KL Divergence Between Gaussians: A Step-by-Step Derivation for the Variational Autoencoder Objective

arXiv:2604.11744v1 Announce Type: new Abstract: Kullback-Leibler (KL) divergence is a fundamental concept in information theory that quantifies the discrepancy between two probability distributions. I

tutorialsarxiv-cs-lg

KSDiff: Keyframe-Augmented Speech-Aware Dual-Path Diffusion for Facial Animation

arXiv:2509.20128v2 Announce Type: replace-cross Abstract: Audio-driven facial animation has made significant progress in multimedia applications, with diffusion models showing strong potential for tal

Applications

Learnable Motion-Focused Tokenization for Effective and Efficient Video Unsupervised Domain Adaptation

arXiv:2604.09955v1 Announce Type: new Abstract: Video Unsupervised Domain Adaptation (VUDA) poses a significant challenge in action recognition, requiring the adaptation of a model from a labeled sour

applicationsarxiv-cs-cv