Search: “retrieval”

ALL-FEM: Agentic Large Language models Fine-tuned for Finite Element Methods

arXiv:2603.21011v2 Announce Type: replace-cross Abstract: Finite element (FE) analysis guides the design and verification of nearly all manufactured objects. It is at the core of computational enginee

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ARGen: Affect-Reinforced Generative Augmentation towards Vision-based Dynamic Emotion Perception

DGX agent

arXiv:2604.12255v1 Announce Type: cross Abstract: Dynamic facial expression recognition in the wild remains challenging due to data scarcity and long-tail distributions, which hinder models from effec

safetyarxiv-cs-ai

15 Apr 2026

Beyond Majority Voting: Efficient Best-Of-N with Radial Consensus Score

arXiv:2604.12196v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate multiple candidate responses for a given prompt, yet selecting the most reliable one remains challengin

agentsarxiv-cs-cl

Beyond Prompt: Fine-grained Simulation of Cognitively Impaired Standardized Patients via Stochastic Steering

arXiv:2604.12210v1 Announce Type: new Abstract: Simulating Standardized Patients with cognitive impairment offers a scalable and ethical solution for clinical training. However, existing methods rely

Building evidence-based knowledge bases from full-text literature for disease-specific biomedical reasoning

arXiv:2603.28325v3 Announce Type: replace-cross Abstract: Biomedical knowledge resources often either preserve evidence as unstructured text or compress it into flat triples that omit study design, pr

CODESTRUCT: Code Agents over Structured Action Spaces

arXiv:2604.05407v2 Announce Type: replace Abstract: LLM-based code agents treat repositories as unstructured text, applying edits through brittle string matching that frequently fails due to formattin

CoG: Controllable Graph Reasoning via Relational Blueprints and Failure-Aware Refinement over Knowledge Graphs

arXiv:2601.11047v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities but often grapple with reliability challenges like hallucinations.

researcharxiv-cs-cl

Continuous Knowledge Metabolism: Generating Scientific Hypotheses from Evolving Literature

arXiv:2604.12243v1 Announce Type: cross Abstract: Scientific hypothesis generation requires tracking how knowledge evolves, not just what is currently known. We introduce Continuous Knowledge Metaboli

DecompSR: A dataset for decomposed analyses of compositional multihop spatial reasoning

arXiv:2511.02627v2 Announce Type: replace Abstract: We introduce DecompSR, decomposed spatial reasoning, a large benchmark dataset (over 5m datapoints) and generation framework designed to analyse com

DeepTest Tool Competition 2026: Benchmarking an LLM-Based Automotive Assistant

arXiv:2604.12615v1 Announce Type: new Abstract: This report summarizes the results of the first edition of the Large Language Model (LLM) Testing competition, held as part of the DeepTest workshop at

Drawing on Memory: Dual-Trace Encoding Improves Cross-Session Recall in LLM Agents

arXiv:2604.12948v1 Announce Type: new Abstract: LLM agents with persistent memory store information as flat factual records, providing little context for temporal reasoning, change tracking, or cross-

EMBER: Autonomous Cognitive Behaviour from Learned Spiking Neural Network Dynamics in a Hybrid LLM Architecture

arXiv:2604.12167v1 Announce Type: new Abstract: We present (Experience-Modulated Biologically-inspired Emergent Reasoning), a hybrid cognitive architecture that reorganises the relationship between la

Empirical Evaluation of PDF Parsing and Chunking for Financial Question Answering with RAG

model-releasesarxiv-cs-cl

arXiv:2604.12047v1 Announce Type: new Abstract: PDF files are primarily intended for human reading rather than automated processing. In addition, the heterogeneous content of PDFs, such as text, table

From Myopic Selection to Long-Horizon Awareness: Sequential LLM Routing for Multi-Turn Dialogue

arXiv:2604.12385v1 Announce Type: new Abstract: Multi-turn dialogue is the predominant form of interaction with large language models (LLMs). While LLM routing is effective in single-turn settings, ex

safetyarxiv-cs-cl

Fully Homomorphic Encryption on Llama 3 model for privacy preserving LLM inference

arXiv:2604.12168v1 Announce Type: cross Abstract: The applications of Generative Artificial Intelligence (GenAI) and their intersections with data-driven fields, such as healthcare, finance, transport

HintMR: Eliciting Stronger Mathematical Reasoning in Small Language Models

arXiv:2604.12229v1 Announce Type: new Abstract: Small language models (SLMs) often struggle with complex mathematical reasoning due to limited capacity to maintain long chains of intermediate steps an

local-aiarxiv-cs-ai

Is Sliding Window All You Need? An Open Framework for Long-Sequence Recommendation

arXiv:2604.12372v1 Announce Type: new Abstract: Long interaction histories are central to modern recommender systems, yet training with long sequences is often dismissed as impractical under realistic

researcharxiv-cs-lg

KG-Hopper: Empowering Compact Open LLMs with Knowledge Graph Reasoning via Reinforcement Learning

arXiv:2603.21440v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate impressive natural language capabilities but often struggle with knowledge-intensive reasoning tasks.

Learning Chain Of Thoughts Prompts for Predicting Entities, Relations, and even Literals on Knowledge Graphs

arXiv:2604.12651v1 Announce Type: cross Abstract: Knowledge graph embedding (KGE) models perform well on link prediction but struggle with unseen entities, relations, and especially literals, limiting

LLM as Attention-Informed NTM and Topic Modeling as long-input Generation: Interpretability and long-Context Capability

arXiv:2510.03174v2 Announce Type: replace-cross Abstract: Topic modeling aims to produce interpretable topic representations and topic--document correspondences from corpora, but classical neural topi

Applications

LLM-HYPER: Generative CTR Modeling for Cold-Start Ad Personalization via LLM-Based Hypernetworks

arXiv:2604.12096v1 Announce Type: new Abstract: On online advertising platforms, newly introduced promotional ads face the cold-start problem, as they lack sufficient user feedback for model training.

applicationsarxiv-cs-ai

Lyra 2.0: Explorable Generative 3D Worlds

arXiv:2604.13036v1 Announce Type: new Abstract: Recent advances in video generation enable a new paradigm for 3D scene creation: generating camera-controlled videos that simulate scene walkthroughs, t

researcharxiv-cs-cv

Masked by Consensus: Disentangling Privileged Knowledge in LLM Correctness

arXiv:2604.12373v1 Announce Type: new Abstract: Humans use introspection to evaluate their understanding through private internal states inaccessible to external observers. We investigate whether larg

local-aiarxiv-cs-cl

MISID: A Multimodal Multi-turn Dataset for Complex Intent Recognition in Strategic Deception Games

arXiv:2604.12700v1 Announce Type: new Abstract: Understanding human intent in complex multi-turn interactions remains a fundamental challenge in human-computer interaction and behavioral analysis. Whi

MolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization

arXiv:2604.12237v1 Announce Type: cross Abstract: In drug discovery, molecular optimization aims to iteratively refine a lead compound to improve molecular properties while preserving structural simil

Not All Turns Are Equally Hard: Adaptive Thinking Budgets For Efficient Multi-Turn Reasoning

arXiv:2604.05164v2 Announce Type: replace-cross Abstract: As LLM reasoning performance plateau, improving inference-time compute efficiency is crucial to mitigate overthinking and long thinking traces

Public Profile Matters: A Scalable Integrated Approach to Recommend Citations in the Wild

arXiv:2603.17361v2 Announce Type: replace-cross Abstract: Proper citation of relevant literature is essential for contextualising and validating scientific contributions. While current citation recomm

TempR1: Improving Temporal Understanding of MLLMs via Temporal-Aware Multi-Task Reinforcement Learning

arXiv:2512.03963v3 Announce Type: replace Abstract: Enhancing the temporal understanding of Multimodal Large Language Models (MLLMs) is essential for advancing long-form video analysis, enabling tasks

local-aiarxiv-cs-cv

TIPSv2: Advancing Vision-Language Pretraining with Enhanced Patch-Text Alignment

model-releasesarxiv-cs-cv

arXiv:2604.12012v1 Announce Type: new Abstract: Recent progress in vision-language pretraining has enabled significant improvements to many downstream computer vision applications, such as classificat

ABot-Claw: A Foundation for Persistent, Cooperative, and Self-Evolving Robotic Agents

arXiv:2604.10096v1 Announce Type: new Abstract: Current embodied intelligent systems still face a substantial gap between high-level reasoning and low-level physical execution in open-world environmen

local-aiarxiv-cs-cv

ACE-Bench: A Lightweight Benchmark for Evaluating Azure SDK Usage Correctness

arXiv:2604.09564v1 Announce Type: cross Abstract: We present ACE-Bench (Azure SDK Coding Evaluation Benchmark), an execution-free benchmark that provides fast, reproducible pass or fail signals for wh

ACE-TA: An Agentic Teaching Assistant for Grounded Q&A, Quiz Generation, and Code Tutoring

arXiv:2604.09572v1 Announce Type: cross Abstract: We introduce ACE-TA, the Agentic Coding and Explanations Teaching Assistant framework, that autonomously routes conceptual queries drawn from programm

ADAM: A Systematic Data Extraction Attack on Agent Memory via Adaptive Querying

arXiv:2604.09747v1 Announce Type: cross Abstract: Large Language Model (LLM) agents have achieved rapid adoption and demonstrated remarkable capabilities across a wide range of applications. To improv

Breaking the KV Cache Bottleneck: Fan Duality Model Achieves O(1) Decode Memory with Superior Associative Recall

arXiv:2604.07716v2 Announce Type: replace Abstract: We present FDM (Fan Duality Model), a linear sequence architecture that resolves the fundamental tension between memory efficiency and associative r

researcharxiv-cs-lg

Byte-level generative predictions for forensics multimedia carving

arXiv:2604.11010v1 Announce Type: new Abstract: Digital forensic investigations often face significant challenges when recovering fragmented multimedia files that lack file system metadata. While trad

researcharxiv-cs-cv

Can Multi-Modal LLMs Provide Live Step-by-Step Task Guidance?

model-releasesarxiv-cs-cv

arXiv:2511.21998v2 Announce Type: replace Abstract: Multi-modal Large Language Models (LLM) have advanced conversational abilities but struggle with providing live, interactive step-by-step guidance,

CARINOX: Inference-time Scaling with Category-Aware Reward-based Initial Noise Optimization and Exploration

model-releasesarxiv-cs-cl

arXiv:2509.17458v3 Announce Type: replace-cross Abstract: Text-to-image diffusion models, such as Stable Diffusion, can produce high-quality and diverse images but often fail to achieve compositional

Hardware

CASK: Core-Aware Selective KV Compression for Reasoning Traces

arXiv:2604.10900v1 Announce Type: new Abstract: In large language models performing long-form reasoning, the KV cache grows rapidly with decode length, creating bottlenecks in memory and inference sta

hardwarearxiv-cs-ai

Applications

CHAIRO: Contextual Hierarchical Analogical Induction and Reasoning Optimization for LLMs

arXiv:2604.10502v1 Announce Type: new Abstract: Content moderation in online platforms faces persistent challenges due to the evolving complexity of user-generated content and the limitations of tradi

applicationsarxiv-cs-ai

ChatInject: Abusing Chat Templates for Prompt Injection in LLM Agents

arXiv:2509.22830v3 Announce Type: replace Abstract: The growing deployment of large language model (LLM) based agents that interact with external environments has created new attack surfaces for adver

agentsarxiv-cs-cl

CircuitSynth: Reliable Synthetic Data Generation

arXiv:2604.10114v1 Announce Type: cross Abstract: The generation of high-fidelity synthetic data is a cornerstone of modern machine learning, yet Large Language Models (LLMs) frequently suffer from ha

Claim2Vec: Embedding Fact-Check Claims for Multilingual Similarity and Clustering

arXiv:2604.09812v1 Announce Type: new Abstract: Recurrent claims present a major challenge for automated fact-checking systems designed to combat misinformation, especially in multilingual settings. W

safetyarxiv-cs-cl

Concept Drift Guided LayerNorm Tuning for Efficient Multimodal Metaphor Identification

model-releasesarxiv-cs-lg

arXiv:2505.11237v3 Announce Type: replace-cross Abstract: Metaphorical imagination, the ability to connect seemingly unrelated concepts, is fundamental to human cognition and communication. While unde

Decision-Theoretic Safety Assessment of Persona-Driven Multi-Agent Systems in O-RAN

arXiv:2604.09682v1 Announce Type: cross Abstract: Autonomous network management in Open Radio Access Networks requires intelligent decision making across conflicting objectives, yet existing LLM based

DeCoVec: Building Decoding Space based Task Vector for Large Language Models via In-Context Learning

arXiv:2604.11129v1 Announce Type: new Abstract: Task vectors, representing directions in model or activation spaces that encode task-specific behaviors, have emerged as a promising tool for steering l

researcharxiv-cs-cl

DeepReviewer 2.0: A Traceable Agentic System for Auditable Scientific Peer Review

arXiv:2604.09590v1 Announce Type: new Abstract: Automated peer review is often framed as generating fluent critique, yet reviewers and area chairs need judgments they can audit: where a concern applie

Dialectic-Med: Mitigating Diagnostic Hallucinations via Counterfactual Adversarial Multi-Agent Debate

arXiv:2604.11258v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) in healthcare suffer from severe confirmation bias, often hallucinating visual details to support initial, pote

safetyarxiv-cs-cl

Differentiable Vector Quantization for Rate-Distortion Optimization of Generative Image Compression

arXiv:2604.10546v1 Announce Type: new Abstract: The rapid growth of visual data under stringent storage and bandwidth constraints makes extremely low-bitrate image compression increasingly important.

researcharxiv-cs-cv