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arXiv:2607.20556v1 Announce Type: new Abstract: In large-scale text analysis tasks, pre-trained language models are often used to embed text corpora for downstream analysis. However, such models may s

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Research

Knowledge Injection Exists in MoE? Exploring Expert-Aware Contrast Decoding in MoE for Mitigating LLMs'Hallucinations

DGX agent

arXiv:2607.20426v1 Announce Type: cross Abstract: Existing LLM hallucination mitigation methods, including prompt engineering and model optimization, either hardly alter models'internal knowledge or h

researcharxiv-cs-ai

24 Jul 2026

Hardware

KroQuant: Kronecker-Structured Block Transforms for Efficient Post-Training Quantization of Diffusion Transformers

arXiv:2607.21446v1 Announce Type: cross Abstract: Post-training quantization (PTQ) of diffusion transformers (DiTs) to W4A4 severely degrades output quality, because activations entering each linear l

hardwarearxiv-cs-cv

Latent Variable-Mediated Cross-Learning for Few-Shot Acoustic Impedance Imaging

arXiv:2607.20989v1 Announce Type: new Abstract: Acoustic impedance imaging is a fundamental yet severely ill-posed problem in subsurface analysis: the seismic wavelet is unknown, observations are band

Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timing

arXiv:2607.20723v1 Announce Type: cross Abstract: This work presents LeakyLMs, a set of attacks that leak proprietary model, architecture, and deployment information from production language models. L

LeanFlow: A Case Study in Workflow-Driven Lean Autoformalization

arXiv:2607.20503v1 Announce Type: new Abstract: We present and evaluate LeanFlow, an LLM agent system specialized for translating mathematical papers into buildable Lean projects. Recent verifier-in-t

Learn2Zinc: Fine-tuning Small Language Models for Text-to-Model Translation in MiniZinc

arXiv:2607.20456v1 Announce Type: cross Abstract: Large language models excel at code generation for mainstream programming languages but struggle with rare, domain-specific languages such as MiniZinc

Learning-based Seam Correspondence Reconstruction in Sewing Patterns

arXiv:2607.21213v1 Announce Type: new Abstract: Digital sewing patterns typically consist of disjoint 2D panels without explicit stitch annotations, making downstream 3D modeling reliant on labor-inte

Applications

Learning to Detect UI Principle Violations via Reinforcement Learning

arXiv:2607.20690v1 Announce Type: new Abstract: Small language models and coding agents increasingly generate web front-end code, yet their outputs are typically evaluated primarily for functional cor

applicationsarxiv-cs-cl

Learning to Navigate Efficiently with Only 0.58M Trainable Parameters

model-releasesarxiv-cs-cv

arXiv:2607.11029v2 Announce Type: replace-cross Abstract: Recent progress in visual navigation has largely been driven by scale: end-to-end policies with hundreds of millions of parameters trained on

LegalCiteTrust: Benchmarking Citation Trustworthiness in Chinese Long-Form Legal Research Reports

model-releasesarxiv-cs-cl

arXiv:2607.20872v1 Announce Type: new Abstract: Long-form legal research reports increasingly rely on LLMs and agentic research systems, but their reliability depends not only on answering the task, b

Lessons and Open Questions from a Unified Study of Camera-Trap Species Recognition Over Time

model-releasesarxiv-cs-cv

arXiv:2603.20509v2 Announce Type: replace Abstract: Camera traps are vital for large-scale biodiversity monitoring, yet accurate automated analysis remains challenging due to diverse deployment enviro

Leveraging Biokinetic Knowledge Priors for Data-Scarce Bioprocess Modeling

arXiv:2607.20539v1 Announce Type: cross Abstract: While deep learning has accelerated drug discovery, its impact on biomanufacturing has been considerably more limited. The reason is data scarcity. Bi

tutorialsarxiv-cs-ai

LinearARD: Linear-Memory Attention Distillation for RoPE Restoration

arXiv:2604.00004v2 Announce Type: replace-cross Abstract: The extension of context windows in Large Language Models is typically facilitated by scaling positional encodings followed by lightweight Con

LLM-INSTRUCT at UZH Shared Task 2026: Constraint-Aware Retrieval and Selective Debate for Paragraph-Level Argument Mining

arXiv:2607.20430v1 Announce Type: cross Abstract: We present LLM-INSTRUCT, the winning system for the UZH Shared Task at ArgMining 2026 on paragraph-level argument mining in UN and UNESCO resolutions.

LLMs Get Lost in Evolving User Intent

arXiv:2607.20734v1 Announce Type: new Abstract: As LLMs become more capable, they are increasingly deployed as collaborative agents, taking on user-delegated tasks through iterative interaction. Yet g

tutorialsarxiv-cs-lg

Logic Programming Semantics for Causal Processes

arXiv:2607.21233v1 Announce Type: new Abstract: Motivated by challenging modelling issues in the life sciences, we investigate the relationship between logic programming semantics and the eventual sta

Logical Regression for Planning with Axioms

arXiv:2607.21414v1 Announce Type: new Abstract: In automated planning, logical regression is an operation that returns the most general condition necessary for an action to achieve a particular formul

Loss-Complexity Landscape and Model Structure Functions

arXiv:2507.13543v5 Announce Type: replace-cross Abstract: We develop a framework for dualizing the Kolmogorov structure function h_x(alpha), which then allows using computable complexity proxies. We e

Loss Landscape Topology Reveals Why Simple Baselines are Competitive at 3D Point Cloud Segmentation Under Class Imbalance

arXiv:2607.21089v1 Announce Type: new Abstract: Semantic segmentation of 3D point clouds faces severe class imbalance, yet the effectiveness of specialized imbalance-aware methods from 2D computer vis

M^3-Gen: Interpretable Multimodal Generation of Gene Expression Profiles Using Clinical and Imaging Data

arXiv:2607.21343v1 Announce Type: cross Abstract: Integrating heterogeneous biomedical data, including clinical metadata, histopathology images, and molecular profiles, is crucial for comprehensive di

tutorialsarxiv-cs-ai

Machine-Learned Compact Subspace Generation for Quantum Selected Configuration Interaction within Density Matrix Embedding Framework

arXiv:2607.20585v1 Announce Type: cross Abstract: Sample-based Quantum Diagonalization (SQD), an extension of Quantum Selected Configuration Interaction (QSCI), has emerged as a promising hybrid quant

tutorialsarxiv-cs-lg

Local Ai

Machine Learning for Charge State Characterization of Isolated Double Quantum Dots

arXiv:2607.20871v1 Announce Type: cross Abstract: Scaling semiconductor quantum dot arrays toward fault-tolerant quantum computing requires efficient tuneup of spin qubits, a process that depends on t

local-aiarxiv-cs-lg

MAGE-Vein: Multi-Instance Age and Gender Estimation from Finger Vein Images

arXiv:2607.20897v1 Announce Type: new Abstract: Age estimation from finger vein images has been widely considered impractical due to severe demographic biases in public datasets and physiological conf

MagicMakeup: A Region-Controllable Diffusion Transformer for High-Fidelity Makeup-Transfer

model-releasesarxiv-cs-cv

arXiv:2607.20924v1 Announce Type: new Abstract: Makeup-transfer applies the reference makeup to the source face while preserving the source identity. Despite advances in full-face editing by diffusion

Making Open-Source Text LLM Watermarks Durable Against Merging

arXiv:2607.20435v1 Announce Type: cross Abstract: Open-source LLMs (OSMs)arereaching near state-of-the-art performance, prompting prior works to trace the text they generate by embedding text watermar

tutorialsarxiv-cs-ai

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts

arXiv:2607.20462v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into clinical workflows, stressing the need for reliable traceability of model-generated output

Masked Topology Modeling for Self-Supervised Learning on Parametric CAD

arXiv:2607.20642v1 Announce Type: new Abstract: Computer aided design (CAD) is ubiquitous: virtually any modern object was designed using editable CAD tools. However, with the shortage of available CA

Mean-to-Score Discrete Diffusion: Posterior-Mean Denoisers for Score Entropy

arXiv:2607.21372v1 Announce Type: cross Abstract: Score Entropy Discrete Diffusion (SEDD) parameterizes discrete reverse processes with unconstrained positive score ratios. While positivity guarantees

MedGame: Storytelling Gamification Empowered by Large Language Models for Medical Education

model-releasesarxiv-cs-cl

arXiv:2607.21570v1 Announce Type: new Abstract: Large Language Models (LLMs) show promise for medical education, but most existing systems focus on localized interactions such as question answering or

Safety

MELLA: Bridging Linguistic Capability and Cultural Groundedness for Low-Resource Language MLLMs

arXiv:2508.05502v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) perform strongly in high-resource languages, yet often produce fluent but culturally 'thin' descripti

safetyarxiv-cs-ai

Memoir: Should a Model Write to Its Memory While It Thinks?

arXiv:2607.20792v1 Announce Type: new Abstract: Memoir combines per-sample fast memory, shared slow parameters, variable-depth latent recurrence, and a future-latent energy objective. We test its risk

researcharxiv-cs-lg

Memory-Computation Tradeoffs in Semi Amortized Parametric Optimization

arXiv:2607.20769v1 Announce Type: new Abstract: Learning-enabled decision systems often use offline data or computation to reduce online compute cost. Despite the empirical success of such approaches,

MemTools: A Unified Research Framework for Interoperable Agent Memory

model-releasesarxiv-cs-cl

arXiv:2607.21404v1 Announce Type: new Abstract: While memory systems are essential for agent architectures, pervasive architectural fragmentation restricts systematic research. Existing implementation

MiniCache: Reusable Program Caching with Small Model Interfaces for Efficient LLM Inference

arXiv:2607.20507v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for program-aided reasoning, agentic decision making, and structured task execution, but these applic

Local Ai

Minimum Bayes Risk Decoding for Error Span Detection in Reference-Free Automatic Machine Translation Evaluation

arXiv:2512.07540v4 Announce Type: replace-cross Abstract: Error Span Detection (ESD) extends automatic machine translation (MT) evaluation by localizing translation errors and labeling their severity.

local-aiarxiv-cs-ai

MIRROR: Learning from the Other View for Multi-Modal Reasoning

arXiv:2607.21552v1 Announce Type: new Abstract: Unlike large language models (LLMs) that exhibit strong reasoning capabilities, vision-language models (VLMs) struggle with visual reasoning, even on ge

MKEvolve: A Modular Multi-Agent Framework for Kernel Code Generation

arXiv:2607.20501v1 Announce Type: new Abstract: Despite rapid progress in LLM-based code generation, writing correct and performant kernels for hardware accelerators remains a key bottleneck in scalin

MO-GRPO: Mitigating Reward Hacking of Group Relative Policy Optimization on Multi-Objective Problems

arXiv:2509.22047v3 Announce Type: replace Abstract: Group Relative Policy Optimization (GRPO) has been shown to be an effective algorithm when an accurate reward model is available. However, such a hi

Moir: Let the Model Direct Its Own Story for Robust Cross-Domain Knowledge Editing

arXiv:2607.20433v1 Announce Type: cross Abstract: While language models remain frozen at their training state, the world evolves continuously. Knowledge editing has emerged as a key alternative to ful

Monkey King Bang: A Unified Scientific Multimodal Foundation Model

arXiv:2607.20557v1 Announce Type: cross Abstract: Scientific discovery is increasingly shifting from isolated disciplines to multi-domain reasoning, and AI for science faces a similar transition. Exis

More Is Not More: What Matters for Diversity in LLM Opinions?

arXiv:2607.20429v1 Announce Type: cross Abstract: Large language models are increasingly used to simulate diverse human opinions in open-ended tasks such as synthetic surveys, focus group modeling, an

Hardware

Ms. Forcing: Efficient Streaming Video Generation with Multi-Scale Patchification and Attention

arXiv:2607.20940v1 Announce Type: new Abstract: Streaming video diffusion models have made substantial progress toward interactive and dynamic world simulation, but the nested autoregressive and denoi

hardwarearxiv-cs-cv

Local Ai

MSBraM: A Multi-scale Self-supervised Brain Foundation Model for Hierarchical EEG Dynamics Learning

arXiv:2607.21402v1 Announce Type: new Abstract: Self-supervised foundation models have recently shown strong potential for electroencephalogram (EEG)-based analysis. However, existing approaches strug

local-aiarxiv-cs-ai

Multi-Task Learning for Heterogeneous Prediction from Video Game State with Transfer Learning

arXiv:2607.21290v1 Announce Type: cross Abstract: Multi-task learning (MTL) is a promising approach for prediction tasks derived from video game state data, as modern game telemetry provides multiple

Multi-turn RL with Structural and Performance Aware Rewards for CUDA Kernel Generation

arXiv:2607.20908v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a powerful technique to enhance the reasoning capacity of LLMs for optimized code

Multilevel Graph Wavelet Compressed Sensing with Scale-Aware Neural Recovery

arXiv:2607.20857v1 Announce Type: cross Abstract: Scientific machine learning methods such as neural operators and physics-informed neural networks have advanced engineering applications and inverse p

Multimodal CoLRAG-TF: Triple-Filtered Retrieval for Complex PDFs

arXiv:2607.20517v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) over heterogeneous PDF collections remains challenging due to multimodal content, domain-specific terminology, and