Efficient Inference for Large Vision-Language Models: Bottlenecks, Techniques, and Prospects
arXiv:2604.05546v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) enable sophisticated reasoning over images and videos, yet their inference is hindered by a systemic efficiency barrier known as visual token dominance. This overhead is driven by a multi-regime interplay between...
ClawsBench: Evaluating Capability and Safety of LLM Productivity Agents in Simulated Workspaces
arXiv:2604.05172v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed to automate productivity tasks (e.g., email, scheduling, document management), but evaluating them on live services is risky due to potentially irreversible changes. Existing benchmarks rely on simplified...
A Theoretical Framework for Statistical Evaluability of Generative Models
arXiv:2604.05324v1 Announce Type: new Abstract: Statistical evaluation aims to estimate the generalization performance of a model using held-out i.i.d.\ test data sampled from the ground-truth distribution. In supervised learning settings such as classification, performance metrics such as error rate are...
XMark: Reliable Multi-Bit Watermarking for LLM-Generated Texts
arXiv:2604.05242v1 Announce Type: new Abstract: Multi-bit watermarking has emerged as a promising solution for embedding imperceptible binary messages into Large Language Model (LLM)-generated text, enabling reliable attribution and tracing of malicious usage of LLMs. Despite recent progress, existing methods still...
Bypassing the CSI Bottleneck: MARL-Driven Spatial Control for Reflector Arrays
arXiv:2604.05162v1 Announce Type: new Abstract: Reconfigurable Intelligent Surfaces (RIS) are pivotal for next-generation smart radio environments, yet their practical deployment is severely bottlenecked by the intractable computational overhead of Channel State Information (CSI) estimation. To bypass this fundamental physical-layer barrier,...
Turbulence-like 5/3 spectral scaling in contextual representations of language as a complex system
arXiv:2604.05536v1 Announce Type: new Abstract: Natural language is a complex system that exhibits robust statistical regularities. Here, we represent text as a trajectory in a high-dimensional embedding space generated by transformer-based language models, and quantify scale-dependent fluctuations along the token...
DIA-HARM: Dialectal Disparities in Harmful Content Detection Across 50 English Dialects
arXiv:2604.05318v1 Announce Type: new Abstract: Harmful content detectors-particularly disinformation classifiers-are predominantly developed and evaluated on Standard American English (SAE), leaving their robustness to dialectal variation unexplored. We present DIA-HARM, the first benchmark for evaluating disinformation detection robustness across 50 English...
Non-monotonic causal discovery with Kolmogorov-Arnold Fuzzy Cognitive Maps
arXiv:2604.05136v1 Announce Type: new Abstract: Fuzzy Cognitive Maps constitute a neuro-symbolic paradigm for modeling complex dynamic systems, widely adopted for their inherent interpretability and recurrent inference capabilities. However, the standard FCM formulation, characterized by scalar synaptic weights and monotonic activation...
Thinking Diffusion: Penalize and Guide Visual-Grounded Reasoning in Diffusion Multimodal Language Models
arXiv:2604.05497v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) are emerging as promising alternatives to autoregressive (AR) LLMs. Recently, this paradigm has been extended to multimodal tasks, leading to the development of diffusion multimodal large language models (dMLLMs). These...
From Governance Norms to Enforceable Controls: A Layered Translation Method for Runtime Guardrails in Agentic AI
arXiv:2604.05229v1 Announce Type: new Abstract: Agentic AI systems plan, use tools, maintain state, and produce multi-step trajectories with external effects. Those properties create a governance problem that differs materially from single-turn generative AI: important risks emerge dur- ing execution, not...
Beneath the Surface: Investigating LLMs' Capabilities for Communicating with Subtext
arXiv:2604.05273v1 Announce Type: new Abstract: Human communication is fundamentally creative, and often makes use of subtext -- implied meaning that goes beyond the literal content of the text. Here, we systematically study whether language models can use subtext in communicative...
Operational Noncommutativity in Sequential Metacognitive Judgments
arXiv:2604.04938v1 Announce Type: new Abstract: Metacognition, understood as the monitoring and regulation of one's own cognitive processes, is inherently sequential: an agent evaluates an internal state, updates it, and may then re-evaluate under modified criteria. Order effects in cognition are...
EvolveRouter: Co-Evolving Routing and Prompt for Multi-Agent Question Answering
arXiv:2604.05149v1 Announce Type: new Abstract: Large language model agents often exhibit complementary strengths, making routing a promising approach for multi-agent question answering. However, existing routing methods remain limited in two important ways: they typically optimize over a fixed pool of...
PRIME: Prototype-Driven Multimodal Pretraining for Cancer Prognosis with Missing Modalities
arXiv:2604.04999v1 Announce Type: new Abstract: Multimodal self-supervised pretraining offers a promising route to cancer prognosis by integrating histopathology whole-slide images, gene expression, and pathology reports, yet most existing approaches require fully paired and complete inputs. In practice, clinical cohorts are...
Optimal-Transport-Guided Functional Flow Matching for Turbulent Field Generation in Hilbert Space
arXiv:2604.05700v1 Announce Type: new Abstract: High-fidelity modeling of turbulent flows requires capturing complex spatiotemporal dynamics and multi-scale intermittency, posing a fundamental challenge for traditional knowledge-based systems. While deep generative models, such as diffusion models and Flow Matching, have shown promising...
FNO$^{\angle \theta}$: Extended Fourier neural operator for learning state and optimal control of distributed parameter systems
arXiv:2604.05187v1 Announce Type: new Abstract: We propose an extended Fourier neural operator (FNO) architecture for learning state and linear quadratic additive optimal control of systems governed by partial differential equations. Using the Ehrenpreis-Palamodov fundamental principle, we show that any state...
The Many Ways of Constitutional Discourse
On January 31, 2026, in a stunning three-page order by Judge Fred Biery, the United States District Court for the Western District of Texas granted habeas relief to five-year-old Liam Conejo Ramos and his father Adrian Conejo Arias—who had been...
Learning to Focus: CSI-Free Hierarchical MARL for Reconfigurable Reflectors
arXiv:2604.05165v1 Announce Type: new Abstract: Reconfigurable Intelligent Surfaces (RIS) has a potential to engineer smart radio environments for next-generation millimeter-wave (mmWave) networks. However, the prohibitive computational overhead of Channel State Information (CSI) estimation and the dimensionality explosion inherent in centralized...
Pressure, What Pressure? Sycophancy Disentanglement in Language Models via Reward Decomposition
arXiv:2604.05279v1 Announce Type: new Abstract: Large language models exhibit sycophancy, the tendency to shift their stated positions toward perceived user preferences or authority cues regardless of evidence. Standard alignment methods fail to correct this because scalar reward models conflate two...
Auditable Agents
arXiv:2604.05485v1 Announce Type: new Abstract: LLM agents call tools, query databases, delegate tasks, and trigger external side effects. Once an agent system can act in the world, the question is no longer only whether harmful actions can be prevented--it is...
TDA-RC: Task-Driven Alignment for Knowledge-Based Reasoning Chains in Large Language Models
arXiv:2604.04942v1 Announce Type: new Abstract: Enhancing the reasoning capability of large language models (LLMs) remains a core challenge in natural language processing. The Chain-of-Thought (CoT) paradigm dominates practical applications for its single-round efficiency, yet its reasoning chains often exhibit logical...
Channel-wise Retrieval for Multivariate Time Series Forecasting
arXiv:2604.05543v1 Announce Type: new Abstract: Multivariate time series forecasting often struggles to capture long-range dependencies due to fixed lookback windows. Retrieval-augmented forecasting addresses this by retrieving historical segments from memory, but existing approaches rely on a channel-agnostic strategy that applies...
Dialogue Act Patterns in GenAI-Mediated L2 Oral Practice: A Sequential Analysis of Learner-Chatbot Interactions
arXiv:2604.05702v1 Announce Type: new Abstract: While generative AI (GenAI) voice chatbots offer scalable opportunities for second language (L2) oral practice, the interactional processes related to learners' gains remain underexplored. This study investigates dialogue act (DA) patterns in interactions between Grade...
Same Graph, Different Likelihoods: Calibration of Autoregressive Graph Generators via Permutation-Equivalent Encodings
arXiv:2604.05613v1 Announce Type: new Abstract: Autoregressive graph generators define likelihoods via a sequential construction process, but these likelihoods are only meaningful if they are consistent across all linearizations of the same graph. Segmented Eulerian Neighborhood Trails (SENT), a recent linearization...
Pramana: Fine-Tuning Large Language Models for Epistemic Reasoning through Navya-Nyaya
arXiv:2604.04937v1 Announce Type: new Abstract: Large language models produce fluent text but struggle with systematic reasoning, often hallucinating confident but unfounded claims. When Apple researchers added irrelevant context to mathematical problems, LLM performance degraded by 65% Apple Machine Learning Research,...
Instruction-Tuned LLMs for Parsing and Mining Unstructured Logs on Leadership HPC Systems
arXiv:2604.05168v1 Announce Type: new Abstract: Leadership-class HPC systems generate massive volumes of heterogeneous, largely unstructured system logs. Because these logs originate from diverse software, hardware, and runtime layers, they exhibit inconsistent formats, making structure extraction and pattern discovery extremely challenging....
Vehicle-as-Prompt: A Unified Deep Reinforcement Learning Framework for Heterogeneous Fleet Vehicle Routing Problem
arXiv:2604.05195v1 Announce Type: new Abstract: Unlike traditional homogeneous routing problems, the Heterogeneous Fleet Vehicle Routing Problem (HFVRP) involves heterogeneous fixed costs, variable travel costs, and capacity constraints, rendering solution quality highly sensitive to vehicle selection. Furthermore, real-world logistics applications often...
Rethinking the Key Role of Private Antitrust Enforcement
CoALFake: Collaborative Active Learning with Human-LLM Co-Annotation for Cross-Domain Fake News Detection
arXiv:2604.04174v1 Announce Type: new Abstract: The proliferation of fake news across diverse domains highlights critical limitations in current detection systems, which often exhibit narrow domain specificity and poor generalization. Existing cross-domain approaches face two key challenges: (1) reliance on labelled...