Search: “reasoning”

arXiv:2608.23834v1 Announce Type: new Abstract: The key-value (KV) cache is a primary capacity and bandwidth bottleneck in long-context LLM serving. We present Minima-KV, a retention-preserving hierar

hardwarearxiv-cs-ai

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Mixture of Channel Experts: Static Sparse Supports with Input-Adaptive Mixing for Pointwise Projections

DGX agent

arXiv:2608.23794v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) scales language models by routing each input through a small set of independently parameterized experts. We show that copying

tutorialsarxiv-cs-cv

26 Aug 2026

Names Can Hurt: Spotting Slopsquatting Risks Caused by Package Name Hallucinations in Local Coding LLMs

arXiv:2608.23897v1 Announce Type: cross Abstract: When a code generating language model fabricates a Python package name, an adversary who has pre-registered that name on PyPI can convert that halluci

Panning for Gold: Expanding Domain-Specific Knowledge Graphs with General Knowledge

arXiv:2601.10485v5 Announce Type: replace Abstract: Domain-specific knowledge graphs (DKGs) are critical yet often suffer from limited coverage compared to General Knowledge Graphs (GKGs). Existing ta

QML for Quantum Sensing under Measurement-Induced Information Loss

arXiv:2608.23934v1 Announce Type: cross Abstract: Nitrogen-vacancy (NV) centers in diamond can serve as highly sensitive solid-state quantum sensors for high-sensitivity magnetometry. However, in the

Rules Before Oracles: Auditable, User-Configurable Argument Selection for Deliberative Polling

arXiv:2608.23979v1 Announce Type: new Abstract: In a deliberative poll, once submissions outnumber what anyone will read, some mechanism chooses which arguments each voter sees, acquiring much of the

Scalable and Versatile Identification for Hierarchical Structural Causal Models: A New Look at Project STAR

arXiv:2608.24500v1 Announce Type: cross Abstract: The STAR (Student-Teacher Achievement Ratio) experiment (1985, Tennessee, USA) is a landmark hierarchical dataset designed to assess the impact of cla

Tutorials

Stack Transformer Based Spatial-Temporal Attention Model for Dynamic Sign Language and Fingerspelling Recognition

arXiv:2503.16855v3 Announce Type: replace Abstract: Hand gesture-based Sign Language Recognition (SLR) serves as a crucial communication bridge between deaf and non-deaf individuals. While Graph Convo

tutorialsarxiv-cs-cv

Syn2RealTrack: Bridging the Gap Between Synthetic and Real-World Datasets for Online Multi-View Multi-Target Tracking

arXiv:2608.24130v1 Announce Type: cross Abstract: Multi-camera 3D perception systems for warehouse scenes are trained largely on synthetic data and evaluated on physically captured environments. The r

Too much of a good thing -- when knowledge distillation promotes overfitting, and how to avoid it

arXiv:2608.23752v1 Announce Type: cross Abstract: The growing size of Convolutional Neural Networks has led to increasingly large and costly models. Knowledge Distillation (KD) addresses this by trans

Transformer Accelerator (TFA): A Macro-Op INT8 Hardware Chip for Transformer Inference and Machine Translation

arXiv:2608.23582v1 Announce Type: cross Abstract: We present the Transformer Accelerator (TFA), a synthesizable, parameterizable INT8 memory-to-memory engine for transformer inference. One time-multip

researcharxiv-cs-lg

TransPhy: Visual In-Context Learning for Physically Grounded Image Editing

arXiv:2608.24119v1 Announce Type: cross Abstract: Visual demonstrations provide a natural interface for specifying image transformations that are difficult to describe exhaustively with text. However,

WeMM-Embedding: WeChat Multi-Modal Embedding Technical Report

model-releasesarxiv-cs-cv

arXiv:2608.24053v1 Announce Type: new Abstract: Universal multimodal embeddings are becoming a core component of modern AI systems, enabling heterogeneous content to be represented in a shared space f

AI University: An LLM-Powered Learning Assistant for Engineering---A Finite Element Method Case Study

arXiv:2504.08846v2 Announce Type: replace-cross Abstract: We introduce AI University (AI-U), a flexible framework for AI-driven course content delivery that adapts to a course's instructional style. A

Tutorials

CAI-DLLM: Convergence Aware Inference for Diffusion Language Models

arXiv:2608.22646v1 Announce Type: new Abstract: Diffusion language models can generate many tokens in parallel, but they still require repeated denoising steps during inference. This makes generation

tutorialsarxiv-cs-ai

Coarse Indexing, Fine Evidence: Decoupling Temporal Granularity in Long-Video RAG

arXiv:2608.23011v1 Announce Type: cross Abstract: Graph-based retrieval-augmented generation (RAG) provides a scalable paradigm for long-video understanding, but existing systems typically inherit a f

Agents

Compositional Chain-of-Relations for Faithful Knowledge Graph Question Answering with Large Language Models

arXiv:2608.22762v1 Announce Type: new Abstract: Knowledge graph question answering (KGQA) is a key task for evaluating KG-augmented Large Language Models (LLMs), and complex KGQA that requires multi-h

agentsarxiv-cs-ai

Do Large Language Models Perform Well on Comprehending Poetic Logic in Modern Chinese Poetry?

model-releasesarxiv-cs-cl

arXiv:2608.21827v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved significant progress across a wide range of natural language processing (NLP) tasks, yet their ability to und

ESCRAG-R1: Retrieval-Augmented Reinforcement Learning for Emotional Support Conversation

arXiv:2608.21925v1 Announce Type: new Abstract: Emotional Support Conversation (ESC) systems aim to provide holistic support by balancing professional therapeutic competence with natural empathy. Howe

Evaluation of Small Vision-Language Models on Qualitative Mechanical Problems

arXiv:2608.22143v1 Announce Type: new Abstract: Qualitative mechanical problem-solving (QMPS) refers to solving qualitative problems from the mechanical domain. Qualitative problems can be solved with

EviSafe: Evidence-Grounded Safety Evaluation for Vision-Language Models

arXiv:2608.23313v1 Announce Type: new Abstract: Vision-language model safety benchmarks typically evaluate only final responses: whether a model refuses, warns, or complies. This outcome-level view ca

EvoWiki: Incremental State Overwriting and Traceable Question Answering for Cross-Meeting Knowledge Evolution

model-releasesarxiv-cs-cl

arXiv:2608.23265v1 Announce Type: new Abstract: In long-term collaboration spanning multiple meetings, factual states such as decisions and risks are continually revised, overturned, and replaced. Exi

HERO: Human-profile Enhanced Retrieval Optimization Framework for Long-term Agent Memory

arXiv:2608.22310v1 Announce Type: new Abstract: Long-term memory is crucial for personalized responses and long-horizon agent interactions. Existing methods often rely on LLMs to compress or rewrite d

Hierarchical Book Organization for Learning-Resource Discovery using Dual-Path Graph Convolutions

model-releasesarxiv-cs-lg

arXiv:2512.21076v2 Announce Type: replace-cross Abstract: The growing availability of books and textual materials in digital learning environments necessitates reliable semantic organization to suppor

How AI Assistance Affects Human Skill Development: A Study of Learning with Logic Puzzles

arXiv:2608.23543v1 Announce Type: new Abstract: While AI assistance can improve human task performance in the short term, it may also undermine the development of skills in the longer term. We examine

Iteration Without Elaboration: A Simple ReAct Architecture Suffices for Text-to-SQL Generation

arXiv:2608.22651v1 Announce Type: new Abstract: Modern text-to-SQL systems have become increasingly elaborate, relying on schema-linking modules, retrieval-augmented prompting, candidate generation, a

researcharxiv-cs-cl

Agents

Lagrange: An Open-Vocabulary, Energy-Based Sparse Framework for Generalized End-to-End Driving

arXiv:2606.20274v2 Announce Type: replace Abstract: Scaling end-to-end autonomous driving to complex, open-world environments requires perceptual models that generalize to anomalous scenarios and plan

agentsarxiv-cs-ai

Applications

Loss Landscape Features That Make Adam Stall: Definitions, Estimators, and the Preconditioned Hessian View

arXiv:2608.22145v1 Announce Type: new Abstract: Across implicit-neural-representation (INR) architectures and analytic benchmarks we observe that a thoroughly tuned Adam (especially its learning rate

applicationsarxiv-cs-lg

One Polluted Page Is Enough: Evaluating Web Content Pollution in LLM Recommenders

arXiv:2606.13610v2 Announce Type: replace-cross Abstract: Search-augmented LLMs increasingly mediate everyday consumer recommendations by retrieving live web content. This creates a new risk: LLM reco

Pointing-VLA: Typed Spatial Grounding Interfaces for Vision-Language-Action Manipulation

arXiv:2608.23138v1 Announce Type: cross Abstract: Vision-language-action (VLA) models often expose spatial grounding through autoregressive text coordinates or opaque action tokens, creating brittle i

SlideGen: Collaborative Multimodal Agents for Scientific Slide Generation

arXiv:2512.04529v3 Announce Type: replace Abstract: Creating presentation slides from scientific papers is not simply a matter of summarizing paragraphs. A presenter is required to decide what story t

TO-Agents: A Multi-Agent AI Framework for Subjective Preference-Guided Topology Optimization

arXiv:2605.21622v2 Announce Type: replace Abstract: Topology optimization can generate efficient structures, but designers often must manually translate qualitative intent, such as desired visual styl

Toward Effective and Reliable LLM Agents via Dynamic Ontology

arXiv:2608.22974v1 Announce Type: new Abstract: Large language model (LLM) agents rely heavily on knowledge encoded in model parameters or presented as unstructured context. In domain-specific tasks,

Tutorials

Which Algorithms Can Graph Neural Networks Learn?

arXiv:2602.13106v2 Announce Type: replace-cross Abstract: In recent years, there has been growing interest in understanding neural architectures' ability to learn to execute discrete algorithms, a lin

tutorialsarxiv-cs-ai

AEGIS: Preventing Cross-Domain Resource Abuse in MCP

arXiv:2608.20481v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is an open source JSON-RPC protocol that standardizes how large language models (LLMs) interact with external systems

An ambiguity taxonomy for evaluating large language model performance on clinical registry abstraction: a multi-site prospective study

arXiv:2608.20373v1 Announce Type: new Abstract: Objective: To evaluate large language model (LLM) performance on unprocessed electronic medical record (EMR) data for clinical registry abstraction. Met

researcharxiv-cs-cl

Asymmetric Capacity Allocation in Self-Refinement Pipelines

model-releasesarxiv-cs-lg

arXiv:2608.21345v1 Announce Type: new Abstract: Self-refinement, typically structured as generation, critique, and revision, is a widely adopted paradigm for improving LLM generation and serves as a c

Belief Without Behavior: Measuring the Translation of Theory of Mind into Coordinated Social Action in Vision-Language Models

arXiv:2608.20975v1 Announce Type: new Abstract: Effective social interaction requires agents to translate mental state inferences into coordinated behavioral signals across verbal and nonverbal channe

Designing a Robust LLM-Based Evaluation System for Agentic AI in Drug Discovery Through Human Alignment

model-releasesarxiv-cs-lg

arXiv:2608.21057v1 Announce Type: new Abstract: Agentic large language model (LLM) systems are reshaping scientific workflows in chemistry and drug discovery, but evaluating their open-ended, tool-aug

Difficulty-Aware Semantic-ID Optimization for Generative Recommendation

arXiv:2608.20611v1 Announce Type: new Abstract: Semantic-ID-based generative recommendation casts retrieval and ranking as autoregressive generation over hierarchical item identifiers. A common recipe

Don't Judge Code by Its Cover: Exploring Biases in LLM Judges for Code Evaluation

arXiv:2505.16222v2 Announce Type: replace Abstract: With the growing use of large language models(LLMs) as evaluators, their application has expanded to code evaluation tasks, where they assess the co

safetyarxiv-cs-cl

Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration

arXiv:2603.02760v2 Announce Type: replace-cross Abstract: Diffusion large language models (dLLMs) have recently attracted significant attention for their ability to enhance diversity, controllability,

ForeTime-VLA: Causal Future-Token Distillation from a World Action Model for Conveyor-Belt Manipulation

arXiv:2608.20735v1 Announce Type: new Abstract: Manipulating moving objects requires a policy to anticipate contact events, yet vision-language-action (VLA) policies are commonly fine-tuned from the c

Grounded-Exo2Ego: Structured Semantic Grounding for Robust Exocentric-to-Egocentric Video Generation

arXiv:2608.20534v1 Announce Type: new Abstract: Generating egocentric video from a single exocentric video is an emerging and important topic for AR/VR and physical AI. Compared with conventional nove

researcharxiv-cs-cv

Hadith computational science in the age of large language models: a critical narrative review

arXiv:2608.20364v1 Announce Type: cross Abstract: We examine how hadith computational science is being reshaped by transformer models, retrieval-grounded pipelines, and large language models (LLMs). R

Identify, Locate, Link: End-to-End Key-Value Extraction from Document Images

model-releasesarxiv-cs-cl

arXiv:2608.20868v1 Announce Type: cross Abstract: Document processing pipelines traditionally cascade optical character recognition (OCR) engines with downstream models for structured information extr

Interpretable Multimodal Classification with Linear Discriminant Tree Ensembles

arXiv:2608.20384v1 Announce Type: new Abstract: Multimodal affect and behaviour classifiers that fuse heterogeneous text, audio, and visual streams must simultaneously achieve competitive accuracy and

Latent Ordinal Evidence, Misaligned Outputs: Inference-Time Ordinal Lens Alignment for Multimodal LLMs

arXiv:2608.20999v1 Announce Type: new Abstract: Multimodal LLMs apply the language model interface to visual inputs, where ordinal regression tasks such as age estimation, image quality assessment, an

safetyarxiv-cs-cv