All entries

Beyond a Single Frame: Multi-Frame Spatially Grounded Reasoning Across Volumetric MRI

arXiv:2604.15808v1 Announce Type: cross Abstract: Spatial reasoning and visual grounding are core capabilities for vision-language models (VLMs), yet most medical VLMs produce predictions without tran

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Beyond Distribution Sharpening: The Importance of Task Rewards

DGX agent

arXiv:2604.16259v1 Announce Type: cross Abstract: Frontier models have demonstrated exceptional capabilities following the integration of task-reward-based reinforcement learning (RL) into their train

model-releasesarxiv-cs-ai

20 Apr 2026

Beyond MCQ: An Open-Ended Arabic Cultural QA Benchmark with Dialect Variants

arXiv:2510.24328v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used to answer everyday questions, yet their performance on culturally grounded and dialectal co

Applications

Beyond Passive Viewing: A Pilot Study of a Hybrid Learning Platform Augmenting Video Lectures with Conversational AI

arXiv:2604.15334v1 Announce Type: cross Abstract: The exponential growth of AI education has brought millions of learners to online platforms, yet this massive scale has simultaneously exposed critica

applicationsarxiv-cs-ai

Local Ai

Beyond Single-Model Optimization: Preserving Plasticity in Continual Reinforcement Learning

arXiv:2604.15414v1 Announce Type: cross Abstract: Continual reinforcement learning must balance retention with adaptation, yet many methods still rely on single-model preservation, committing to one e

local-aiarxiv-cs-ai

Beyond Surface Statistics: Robust Conformal Prediction for LLMs via Internal Representations

arXiv:2604.16217v1 Announce Type: cross Abstract: Large language models are increasingly deployed in settings where reliability matters, yet output-level uncertainty signals such as token probabilitie

Beyond Text Prompts: Precise Concept Erasure through Text-Image Collaboration

arXiv:2604.15829v1 Announce Type: new Abstract: Text-to-image generative models have achieved impressive fidelity and diversity, but can inadvertently produce unsafe or undesirable content due to impl

Bilevel Optimization of Agent Skills via Monte Carlo Tree Search

arXiv:2604.15709v1 Announce Type: new Abstract: Agent exttt{skills} are structured collections of instructions, tools, and supporting resources that help large language model (LLM) agents perform part

agentsarxiv-cs-ai

BioHiCL: Hierarchical Multi-Label Contrastive Learning for Biomedical Retrieval with MeSH Labels

arXiv:2604.15591v1 Announce Type: cross Abstract: Effective biomedical information retrieval requires modeling domain semantics and hierarchical relationships among biomedical texts. Existing biomedic

Brain Score Tracks Shared Properties of Languages: Evidence from Many Natural Languages and Structured Sequences

arXiv:2604.15503v1 Announce Type: new Abstract: Recent breakthroughs in language models (LMs) using neural networks have raised the question: how similar are these models' processing to human language

Breaking the Training Barrier of Billion-Parameter Universal Machine Learning Interatomic Potentials

model-releasesarxiv-cs-lg

arXiv:2604.15821v1 Announce Type: cross Abstract: Universal Machine Learning Interatomic Potentials (uMLIPs), pre-trained on massively diverse datasets encompassing inorganic materials and organic mol

Breakout-picker: Reducing false positives in deep learning-based borehole breakout characterization from acoustic image logs

arXiv:2604.16011v1 Announce Type: new Abstract: Borehole breakouts are stress-induced spalling on the borehole wall, which are identifiable in acoustic image logs as paired zones with near-symmetry az

Tutorials

Bridging the phenotype-target gap for molecular generation via multi-objective reinforcement learning

arXiv:2509.21010v2 Announce Type: replace-cross Abstract: The de novo generation of drug-like molecules capable of inducing desirable phenotypic changes is receiving increasing attention. However, pre

tutorialsarxiv-cs-ai

Bureaucratic Silences: What the Canadian AI Register Reveals, Omits, and Obscures

arXiv:2604.15514v1 Announce Type: new Abstract: In November 2025, the Government of Canada operationalized its commitment to transparency by releasing its first Federal AI Register. In this paper, we

C-Mining: Unsupervised Discovery of Seeds for Cultural Data Synthesis via Geometric Misalignment

arXiv:2604.15675v1 Announce Type: new Abstract: Achieving cultural alignment in Large Language Models (LLMs) increasingly depends on synthetic data generation. For such synthesis, the most vital initi

safetyarxiv-cs-cl

Can LLMs Understand the Impact of Trauma? Costs and Benefits of LLMs Coding the Interviews of Firearm Violence Survivors

arXiv:2604.16132v1 Announce Type: cross Abstract: Firearm violence is a pressing public health issue, yet research into survivors' lived experiences remains underfunded and difficult to scale. Qualita

Capture the Flags: Family-Based Evaluation of Agentic LLMs via Semantics-Preserving Transformations

arXiv:2602.05523v2 Announce Type: replace-cross Abstract: Agentic large language models (LLMs) are increasingly evaluated on cybersecurity tasks using capture-the-flag (CTF) benchmarks, yet existing p

agentsarxiv-cs-ai

CASR: A Robust Cyclic Framework for Arbitrary Large-Scale Super-Resolution with Distribution Alignment and Self-Similarity Awareness

arXiv:2602.22159v2 Announce Type: replace Abstract: Arbitrary-Scale SR (ASISR) remains fundamentally limited by cross-scale distribution shift: once the inference scale leaves the training range, nois

safetyarxiv-cs-cv

Causal Bootstrapped Alignment for Unsupervised Video-Based Visible-Infrared Person Re-Identification

arXiv:2604.15631v1 Announce Type: new Abstract: VVI-ReID is a critical technique for all-day surveillance, where temporal information provides additional cues beyond static images. However, existing a

safetyarxiv-cs-cv

Chain-of-Thought Degrades Visual Spatial Reasoning Capabilities of Multimodal LLMs

arXiv:2604.16060v1 Announce Type: cross Abstract: Multimodal Reasoning Models (MRMs) leveraging Chain-of-Thought (CoT) based thinking have revolutionized mathematical and logical problem-solving. Howe

Characterising LLM-Generated Competency Questions: a Cross-Domain Empirical Study using Open and Closed Models

arXiv:2604.16258v1 Announce Type: new Abstract: Competency Questions (CQs) are a cornerstone of requirement elicitation in ontology engineering. CQs represent requirements as a set of natural language

ChatENV: An Interactive Vision-Language Model for Sensor-Guided Environmental Monitoring and Scenario Simulation

model-releasesarxiv-cs-cv

arXiv:2508.10635v3 Announce Type: replace Abstract: Understanding environmental changes from remote sensing imagery is vital for climate resilience, urban planning, and ecosystem monitoring. Yet, curr

ChemAmp: Amplified Chemistry Tools via Composable Agents

arXiv:2505.21569v3 Announce Type: replace-cross Abstract: Although LLM-based agents are proven to master tool orchestration in scientific fields, particularly chemistry, their single-task performance

agentsarxiv-cs-ai

ChemGraph-XANES: An Agentic Framework for XANES Simulation and Analysis

arXiv:2604.16205v1 Announce Type: cross Abstract: Computational X-ray absorption near-edge structure (XANES) is widely used to probe local coordination environments, oxidation states, and electronic s

CHOP: Chunkwise Context-Preserving Framework for RAG on Multi Documents

model-releasesarxiv-cs-cl

arXiv:2604.15802v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems lose retrieval accuracy when similar documents coexist in the vector database, causing unnecessary informat

CIG: Measuring Conversational Information Gain in Deliberative Dialogues with Semantic Memory Dynamics

arXiv:2604.15647v1 Announce Type: new Abstract: Measuring the quality of public deliberation requires evaluating not only civility or argument structure, but also the informational progress of a conve

CiPO: Counterfactual Unlearning for Large Reasoning Models through Iterative Preference Optimization

arXiv:2604.15847v1 Announce Type: new Abstract: Machine unlearning has gained increasing attention in recent years, as a promising technique to selectively remove unwanted privacy or copyrighted infor

CLewR: Curriculum Learning with Restarts for Machine Translation Preference Learning

arXiv:2601.05858v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated competitive performance in zero-shot multilingual machine translation (MT). Some follow-up work

CLIMB: Controllable Longitudinal Brain Image Generation using Mamba-based Latent Diffusion Model and Gaussian-aligned Autoencoder

arXiv:2604.15611v1 Announce Type: cross Abstract: Latent diffusion models have emerged as powerful generative models in medical imaging, enabling the synthesis of high quality brain magnetic resonance

Closing the Theory-Practice Gap in Spiking Transformers via Effective Dimension

arXiv:2604.15769v1 Announce Type: cross Abstract: Spiking transformers achieve competitive accuracy with conventional transformers while offering 38-57imes energy efficiency on neuromorphic hardware,

CLOTH-HUGS: Cloth Aware Human Gaussian Splatting

arXiv:2604.15875v1 Announce Type: new Abstract: We present Cloth-HUGS, a Gaussian Splatting based neural rendering framework for photorealistic clothed human reconstruction that explicitly disentangle

CodeMMR: Bridging Natural Language, Code, and Image for Unified Retrieval

arXiv:2604.15663v1 Announce Type: cross Abstract: Code search, framed as information retrieval (IR), underpins modern software engineering and increasingly powers retrieval-augmented generation (RAG),

COEVO: Co-Evolutionary Framework for Joint Functional Correctness and PPA Optimization in LLM-Based RTL Generation

arXiv:2604.15001v2 Announce Type: replace Abstract: LLM-based RTL code generation methods increasingly target both functional correctness and PPA quality, yet existing approaches universally decouple

CoEvolve: Training LLM Agents via Agent-Data Mutual Evolution

arXiv:2604.15840v1 Announce Type: new Abstract: Reinforcement learning for LLM agents is typically conducted on a static data distribution, which fails to adapt to the agent's evolving behavior and le

agentsarxiv-cs-cl

Cognitive Agency Surrender: Defending Epistemic Sovereignty via Scaffolded AI Friction

arXiv:2603.21735v2 Announce Type: replace-cross Abstract: The proliferation of Generative Artificial Intelligence has transformed benign cognitive offloading into a systemic risk of cognitive agency s

safetyarxiv-cs-ai

Collaboration of Fusion and Independence: Hypercomplex-driven Robust Multi-Modal Knowledge Graph Completion

arXiv:2509.23714v2 Announce Type: replace Abstract: Multi-modal knowledge graph completion (MMKGC) aims to discover missing facts in multi-modal knowledge graphs (MMKGs) by leveraging both structural

Collaborative Filtering Through Weighted Similarities of User and Item Embeddings

arXiv:2604.15573v1 Announce Type: cross Abstract: In recent years, neural networks and other complex models have dominated recommender systems, often setting new benchmarks for state-of-the-art perfor

researcharxiv-cs-lg

Collective Kernel EFT for Pre-activation ResNets

arXiv:2604.15742v1 Announce Type: new Abstract: In finite-width deep neural networks, the empirical kernel G evolves stochastically across layers. We develop a collective kernel effective field theory

researcharxiv-cs-lg

CollideNet: Hierarchical Multi-scale Video Representation Learning with Disentanglement for Time-To-Collision Forecasting

arXiv:2604.16240v1 Announce Type: new Abstract: Time-to-Collision (TTC) forecasting is a critical task in collision prevention, requiring precise temporal prediction and comprehending both local and g

CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling

arXiv:2602.01766v2 Announce Type: replace-cross Abstract: The quadratic complexity and indefinitely growing key-value (KV) cache of standard Transformers pose a major barrier to long-context processin

Comparing the latent features of universal machine-learning interatomic potentials

arXiv:2512.05717v3 Announce Type: replace-cross Abstract: The past few years have seen the development of ``universal'' machine-learning interatomic potentials (uMLIPs) capable of approximating the gr

safetyarxiv-cs-lg

Comparison Study: Glacier Calving Front Delineation in Synthetic Aperture Radar Images With Deep Learning

arXiv:2501.05281v2 Announce Type: replace Abstract: Continuous monitoring of glacier calving fronts is essential for sea level rise projections. This study benchmarks Deep Learning systems for front d

COMPASS: Benchmarking Constrained Optimization in LLM Agents

model-releasesarxiv-cs-lg

arXiv:2510.07043v2 Announce Type: replace Abstract: Human decision-making often involves constrained optimization. As LLM agents are deployed to assist with real-world tasks like travel planning, shop

Concept-wise Attention for Fine-grained Concept Bottleneck Models

arXiv:2604.15748v1 Announce Type: new Abstract: Recently impressive performance has been achieved in Concept Bottleneck Models (CBM) by utilizing the image-text alignment learned by a large pre-traine

safetyarxiv-cs-cv

ConFu: Contemplate the Future for Better Speculative Sampling

model-releasesarxiv-cs-cl

arXiv:2603.08899v2 Announce Type: replace Abstract: Speculative decoding has emerged as a powerful approach to accelerate large language model (LLM) inference by employing lightweight draft models to

ConlangCrafter: Constructing Languages with a Multi-Hop LLM Pipeline

arXiv:2508.06094v4 Announce Type: replace Abstract: Constructed languages (conlangs) such as Esperanto and Quenya have played diverse roles in art, philosophy, and international communication. Meanwhi

Consistency Analysis of Sentiment Predictions using Syntactic & Semantic Context Assessment Summarization (SSAS)

arXiv:2604.15547v1 Announce Type: cross Abstract: The fundamental challenge of using Large Language Models (LLMs) for reliable, enterprise-grade analytics, such as sentiment prediction, is the conflic

Constant-Factor Approximations for Doubly Constrained Fair k-Center, k-Median and k-Means

arXiv:2604.16061v1 Announce Type: cross Abstract: We study discrete k-clustering problems in general metric spaces that are constrained by a combination of two different fairness conditions within the

safetyarxiv-cs-lg