Instruction Set and Language for Hypergraphs
arXiv:2607.10194v1 Announce Type: new Abstract: We present IsalHG, a method for representing the structure of any finite, connected hypergraph of bounded hyperedge arity as a string…
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Sense and Sensitivity: Examining the Influence of Semantic Recall on Long Context Code Understanding
arXiv:2505.13353v5 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed for understanding large codebases, but whether they understand operational semantics of long code context…
Cost of Reasoning in non-English Languages: A Case Study on Japanese
arXiv:2607.10114v1 Announce Type: new Abstract: Reasoning Language Models (RLMs) achieve their strongest performance when they reason in English, the language for which reasoning-oriented training data is…
Domain-Aware Scaling Laws Uncover Data Synergy
arXiv:2607.11052v1 Announce Type: cross Abstract: Machine learning progress is often attributed to scaling model size and dataset volume, yet the composition of data can be just…
Efficiently Adapting Spoken Language Models for the Singaporean Context
arXiv:2607.10092v1 Announce Type: new Abstract: Spoken language models (SLMs) unify speech perception and reasoning, but adapting them to sensitive domains is underexplored, especially when the original…
Constraint-Aware Hierarchical Search for Regulation-Driven Fine-Grained Classification
arXiv:2607.10588v1 Announce Type: cross Abstract: Tasks such as customs tariff classification, export control categorization, and standards-based equipment coding require assigning an input instance to a fine-grained…
RouteRec: Strict Evaluation of Recommender-Agent Selection and Aggregation
arXiv:2607.09908v1 Announce Type: new Abstract: Recommender systems increasingly face a choice among heterogeneous agents -- collaborative filters, sequential models, content-based retrievers, and LLM-based rerankers -- yet…
Global Merger-Arbitrage Forecasting with Language Models
arXiv:2607.09921v1 Announce Type: new Abstract: We present a language-model forecasting system for merger arbitrage, a specialized high-stakes financial setting in which the task is to predict…
Faithful by Design: Evaluating and Improving LLM-Generated Clinical Trial Summaries for Multi-Stakeholder Audiences
arXiv:2607.09932v1 Announce Type: new Abstract: Large language models are increasingly used to summarize clinical trial results for healthcare providers, patients, and payers, but their tendency to…
Silent Failures in Quantized LLM Reasoning: A Taxonomy-Based Analysis of Hollow Convergence and Failure Mode Shifts
arXiv:2607.09999v1 Announce Type: new Abstract: We show that post-training quantization can silently alter how large language models reason even when task accuracy is preserved. Using a…
Workload-Driven Optimization for On-Device Real-Time Subtitle Translation
arXiv:2607.09957v1 Announce Type: new Abstract: This report studies on-device English-to-Traditional-Chinese subtitle translation for Taiwan under short inputs, short outputs, batch-size-one inference, low latency, and privacy constraints.…
SCOPE-RL: Optimizing Reasoning Paths Before and After Success
arXiv:2607.11506v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) optimizes LLMs using sparse verifiable final-answer rewards. This sparse anchor reliably verifies whether a trajectory…
Robust, Scalable Detection of Text Containment in Large Web-Crawled Corpora
arXiv:2607.10020v1 Announce Type: new Abstract: We present FindMyText, an open-source Python package designed to efficiently assess whether a given text appears, in part or in full,…
Tool-MCoT: Tool Augmented Multimodal Chain-of-Thought for Content Safety Moderation
arXiv:2604.06205v2 Announce Type: replace Abstract: The growth of online platforms and user content requires strong content moderation systems that can handle complex inputs from various media…
BiasLab: A Multilingual Dual-Framing Framework for LLM Bias Measurement, Applied to Workplace and HR Contexts
arXiv:2601.06861v2 Announce Type: replace Abstract: Background: Large language models (LLMs) harbor systematic biases that are particularly consequential in workplace and HR contexts, where their outputs increasingly…
Emotion Recognition in Signers
arXiv:2512.15376v2 Announce Type: replace-cross Abstract: Recognition of signers' emotions suffers from one theoretical challenge and one practical challenge, namely, the overlap between grammatical and affective facial…
PC-Mix: Partial-Component Audio Spoofing Detection under Mixed Speech and Environmental Sound Conditions
arXiv:2607.10345v1 Announce Type: cross Abstract: Recent studies on partial audio spoofing mainly focus on studio-recorded speech with temporal localization of spoofed segments. However, these studies often…
Do All Visual Tokens Matter Equally? Object-Evidence Preserving Token Merging for Vision-Language Retrieval
arXiv:2607.04605v2 Announce Type: replace-cross Abstract: Multi-vector vision-language retrieval preserves fine-grained visual evidence through maximum-similarity late interaction, but dense image-side tokens make storage and scoring expensive. Existing…
Scaffolding the Strategist: Architecture-Dependent Reasoning Interventions in Hotelling Spatial Markets
arXiv:2607.09743v1 Announce Type: new Abstract: We investigate whether structured reasoning interventions improve the strategic economic reasoning of large language models, and whether their effects depend on…
People use fast and flat simulation to reason about new games
arXiv:2510.11503v2 Announce Type: replace-cross Abstract: Games have long been a microcosm for studying planning and reasoning in both natural and artificial intelligence (AI), often focusing on…
A Dynamic Scene Interaction Reasoning Framework for Scene-level Lane-Change Intention and Trajectory Prediction of Multiple Interacting Vehicles
arXiv:2607.09740v1 Announce Type: new Abstract: Safe motion planning in advanced driver-assistance systems and autonomous vehicles requires an accurate understanding of how the surrounding traffic scene is…
SUNTA: Hierarchical Video Prediction with Surprise-based Chunking
arXiv:2607.02087v2 Announce Type: replace Abstract: Hierarchical state-space models (HSSMs) offer a promising approach to long-horizon prediction by segmenting sequences into temporal chunks. However, their performance hinges…
Coresets Before Score Sets: Evaluation-Unsupervised Prompt Subset Selection for LLM Benchmarks
arXiv:2607.09739v1 Announce Type: new Abstract: We study LLM benchmark coreset selection: selecting a small subset of prompts over multiple benchmarks whose induced model scores and rankings…
Measuring AI Ability to Complete Long Software Tasks
arXiv:2503.14499v4 Announce Type: replace Abstract: Despite rapid progress on AI benchmarks, the real-world meaning of benchmark performance remains unclear. To quantify the capabilities of AI systems…