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Polarization by Default: Auditing Recommendation Bias in LLM-Based Content Curation

arXiv:2604.15937v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed to curate and rank human-created content, yet the nature and structure of their biases in these

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Model Releases

PolicyBank: Evolving Policy Understanding for LLM Agents

DGX agent

arXiv:2604.15505v1 Announce Type: cross Abstract: LLM agents operating under organizational policies must comply with authorization constraints typically specified in natural language. In practice, su

model-releasesarxiv-cs-ai

20 Apr 2026

Predicting Where Steering Vectors Succeed

arXiv:2604.15557v1 Announce Type: cross Abstract: Steering vectors work for some concepts and layers but fail for others, and practitioners have no way to predict which setting applies before running

Preference Estimation via Opponent Modeling in Multi-Agent Negotiation

arXiv:2604.15687v1 Announce Type: new Abstract: Automated negotiation in complex, multi-party and multi-issue settings critically depends on accurate opponent modeling. However, conventional numerical

Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All

arXiv:2411.09355v3 Announce Type: replace-cross Abstract: We study the design of iterative combinatorial auctions (ICAs). The main challenge in this domain is that the bundle space grows exponentially

PRL-Bench: A Comprehensive Benchmark Evaluating LLMs' Capabilities in Frontier Physics Research

arXiv:2604.15411v1 Announce Type: cross Abstract: The paradigm of agentic science requires AI systems to conduct robust reasoning and engage in long-horizon, autonomous exploration. However, current s

Pruning Unsafe Tickets: A Resource-Efficient Framework for Safer and More Robust LLMs

arXiv:2604.15780v1 Announce Type: cross Abstract: Machine learning models are increasingly deployed in real-world applications, but even aligned models such as Mistral and LLaVA still exhibit unsafe b

QuantSightBench: Evaluating LLM Quantitative Forecasting with Prediction Intervals

arXiv:2604.15859v1 Announce Type: cross Abstract: Forecasting has become a natural benchmark for reasoning under uncertainty. Yet existing evaluations of large language models remain limited to judgme

Qwen3.5-Omni Technical Report

arXiv:2604.15804v1 Announce Type: new Abstract: In this work, we present Qwen3.5-Omni, the latest advancement in the Qwen-Omni model family. Representing a significant evolution over its predecessor,

Ragged Paged Attention: A High-Performance and Flexible LLM Inference Kernel for TPU

arXiv:2604.15464v1 Announce Type: cross Abstract: Large Language Model (LLM) deployment is increasingly shifting to cost-efficient accelerators like Google's Tensor Processing Units (TPUs), prioritizi

ReactBench: A Benchmark for Topological Reasoning in MLLMs on Chemical Reaction Diagrams

arXiv:2604.15994v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) excel at recognizing individual visual elements and reasoning over simple linear diagrams. However, when faced

Reasoning over Video: Evaluating How MLLMs Extract, Integrate, and Reconstruct Spatiotemporal Evidence

arXiv:2603.13091v2 Announce Type: replace Abstract: The growing interest in embodied agents increases the demand for spatiotemporal video understanding, yet existing benchmarks largely emphasize extra

Reasoning-targeted Jailbreak Attacks on Large Reasoning Models via Semantic Triggers and Psychological Framing

arXiv:2604.15725v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) have demonstrated strong capabilities in generating step-by-step reasoning chains alongside final answers, enabling thei

RedBench: A Universal Dataset for Comprehensive Red Teaming of Large Language Models

arXiv:2601.03699v2 Announce Type: replace Abstract: As large language models (LLMs) become integral to safety-critical applications, ensuring their robustness against adversarial prompts is paramount.

RefereeBench: Are Video MLLMs Ready to be Multi-Sport Referees

arXiv:2604.15736v1 Announce Type: cross Abstract: While Multimodal Large Language Models (MLLMs) excel at generic video understanding, their ability to support specialized, rule-grounded decision-maki

Repurposing 3D Generative Model for Autoregressive Layout Generation

arXiv:2604.16299v1 Announce Type: new Abstract: We introduce LaviGen, a framework that repurposes 3D generative models for 3D layout generation. Unlike previous methods that infer object layouts from

Robustness Verification of Polynomial Neural Networks

arXiv:2602.06105v2 Announce Type: replace-cross Abstract: We study robustness verification of neural networks via metric algebraic geometry. For polynomial neural networks, certifying a robustness rad

RoleConflictBench: A Benchmark of Role Conflict Scenarios for Evaluating LLMs' Contextual Sensitivity

arXiv:2509.25897v2 Announce Type: replace-cross Abstract: People often encounter role conflicts -- social dilemmas where the expectations of multiple roles clash and cannot be simultaneously fulfilled

Sampling-Based Multi-Modal Multi-Robot Multi-Goal Path Planning

model-releasesarxiv-cs-ro

arXiv:2503.03509v3 Announce Type: replace Abstract: In many robotics applications, multiple robots are working in a shared workspace to complete a set of tasks as fast as possible. Such settings can b

Scalable Maximum Entropy Population Synthesis via Persistent Contrastive Divergence

arXiv:2603.27312v2 Announce Type: replace Abstract: Maximum entropy (MaxEnt) modelling provides a principled framework for generating synthetic populations from aggregate census data, without access t

SCHK-HTC: Sibling Contrastive Learning with Hierarchical Knowledge-Aware Prompt Tuning for Hierarchical Text Classification

arXiv:2604.15998v1 Announce Type: new Abstract: Few-shot Hierarchical Text Classification (few-shot HTC) is a challenging task that involves mapping texts to a predefined tree-structured label hierarc

Seed1.8 Model Card: Towards Generalized Real-World Agency

arXiv:2603.20633v3 Announce Type: replace Abstract: We present Seed1.8, a foundation model aimed at generalized real-world agency: going beyond single-turn prediction to multi-turn interaction, tool u

Seeing the imagined: a latent functional alignment in visual imagery decoding from fMRI data

arXiv:2604.15374v1 Announce Type: cross Abstract: Recent progress in visual brain decoding from fMRI has been enabled by large-scale datasets such as the Natural Scenes Dataset (NSD) and powerful diff

Sequential Regression Learning with Randomized Algorithms

arXiv:2507.03759v2 Announce Type: replace-cross Abstract: This paper presents ``randomized SINDy', a sequential machine learning algorithm designed for dynamic data that has a time-dependent structure

Sketch and Text Synergy: Fusing Structural Contours and Descriptive Attributes for Fine-Grained Image Retrieval

arXiv:2604.15735v1 Announce Type: cross Abstract: Fine-grained image retrieval via hand-drawn sketches or textual descriptions remains a critical challenge due to inherent modality gaps. While hand-dr

Social-JEPA: Emergent Geometric Isomorphism

arXiv:2603.02263v2 Announce Type: replace-cross Abstract: World models compress rich sensory streams into compact latent codes that anticipate future observations. We let separate agents acquire such

SocialGrid: A Benchmark for Planning and Social Reasoning in Embodied Multi-Agent Systems

arXiv:2604.16022v1 Announce Type: new Abstract: As Large Language Models (LLMs) transition from text processors to autonomous agents, evaluating their social reasoning in embodied multi-agent settings

Softpick: No Attention Sink, No Massive Activations with Rectified Softmax

arXiv:2504.20966v4 Announce Type: replace Abstract: We introduce softpick, a rectified, not sum-to-one, drop-in replacement for softmax in transformer attention mechanisms that eliminates attention si

Solving Inverse Parametrized Problems via Finite Elements and Extreme Learning Networks

arXiv:2602.14757v2 Announce Type: replace-cross Abstract: We develop an interpolation-based modeling framework for parameter-dependent partial differential equations arising in control, inverse proble

SSFT: A Lightweight Spectral-Spatial Fusion Transformer for Generic Hyperspectral Classification

arXiv:2604.15828v1 Announce Type: new Abstract: Hyperspectral imaging enables fine-grained recognition of materials by capturing rich spectral signatures, but learning robust classifiers is challengin

Stargazer: A Scalable Model-Fitting Benchmark Environment for AI Agents under Astrophysical Constraints

arXiv:2604.15664v1 Announce Type: new Abstract: The rise of autonomous AI agents suggests that dynamic benchmark environments with built-in feedback on scientifically grounded tasks are needed to eval

Stein Variational Black-Box Combinatorial Optimization

arXiv:2604.15837v1 Announce Type: new Abstract: Combinatorial black-box optimization in high-dimensional settings demands a careful trade-off between exploiting promising regions of the search space a

Stochasticity in Tokenisation Improves Robustness

arXiv:2604.16037v1 Announce Type: new Abstract: The widespread adoption of large language models (LLMs) has increased concerns about their robustness. Vulnerabilities in perturbations of tokenisation

Subjective and Objective Quality-of-Experience Evaluation Study for Live Video Streaming

arXiv:2409.17596v2 Announce Type: replace-cross Abstract: In recent years, live video streaming has gained widespread popularity across various social media platforms. Quality of experience (QoE), whi

SwanNLP at SemEval-2026 Task 5: An LLM-based Framework for Plausibility Scoring in Narrative Word Sense Disambiguation

arXiv:2604.16262v1 Announce Type: new Abstract: Recent advances in language models have substantially improved Natural Language Understanding (NLU). Although widely used benchmarks suggest that Large

TabularMath: Understanding Math Reasoning over Tables with Large Language Models

arXiv:2505.19563v4 Announce Type: replace Abstract: Mathematical reasoning has long been a key benchmark for evaluating large language models. Although substantial progress has been made on math word

The Illusion of Equivalence: Systematic FP16 Divergence in KV-Cached Autoregressive Inference

arXiv:2604.15409v1 Announce Type: cross Abstract: KV caching is a ubiquitous optimization in autoregressive transformer inference, long presumed to be numerically equivalent to cache-free computation.

The Metacognitive Monitoring Battery: A Cross-Domain Benchmark for LLM Self-Monitoring

arXiv:2604.15702v1 Announce Type: new Abstract: We introduce a cross-domain behavioural assay of monitoring-control coupling in LLMs, grounded in the Nelson and Narens (1990) metacognitive framework a

The Reasoning Trap: How Enhancing LLM Reasoning Amplifies Tool Hallucination

arXiv:2510.22977v2 Announce Type: replace-cross Abstract: Enhancing the reasoning capabilities of Large Language Models (LLMs) is a key strategy for building Agents that 'think then act.' However, rec

The Relic Condition: When Published Scholarship Becomes Material for Its Own Replacement

arXiv:2604.16116v1 Announce Type: cross Abstract: We extracted the scholarly reasoning systems of two internationally prominent humanities and social science scholars from their published corpora alon

The Spectral Geometry of Thought: Phase Transitions, Instruction Reversal, Token-Level Dynamics, and Perfect Correctness Prediction in How Transformers Reason

arXiv:2604.15350v1 Announce Type: new Abstract: We discover that large language models exhibit spectral phase transitions in their hidden activation spaces when engaging in reasoning versus factual re

Towards Realistic Open-Vocabulary Remote Sensing Segmentation: Benchmark and Baseline

arXiv:2604.15652v1 Announce Type: new Abstract: Open-vocabulary remote sensing image segmentation (OVRSIS) remains underexplored due to fragmented datasets, limited training diversity, and the lack of

Towards Universal Convergence of Backward Error in Linear System Solvers

arXiv:2604.16075v1 Announce Type: cross Abstract: The quest for an algorithm that solves an nimes n linear system in O(n^2) time complexity, or O(n^2 ext{poly}(1/epsilon)) when solving up to epsilon r

Transformer Neural Processes - Kernel Regression

arXiv:2411.12502v4 Announce Type: replace-cross Abstract: Neural Processes (NPs) are a rapidly evolving class of models designed to directly model the posterior predictive distribution of stochastic p

TRIDENT: Enhancing Large Language Model Safety with Tri-Dimensional Diversified Red-Teaming Data Synthesis

arXiv:2505.24672v2 Announce Type: replace Abstract: Large Language Models (LLMs) excel in various natural language processing tasks but remain vulnerable to generating harmful content or being exploit

TwinTrack: Post-hoc Multi-Rater Calibration for Medical Image Segmentation

arXiv:2604.15950v1 Announce Type: new Abstract: Pancreatic ductal adenocarcinoma (PDAC) segmentation on contrast-enhanced CT is inherently ambiguous: inter-rater disagreement among experts reflects ge

Two-Dimensional Deep ReLU CNN Approximation for Korobov Functions: A Constructive Approach

arXiv:2503.07976v2 Announce Type: replace-cross Abstract: This paper investigates approximation capabilities of two-dimensional (2D) deep convolutional neural networks (CNNs), with Korobov functions s

TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models

arXiv:2604.15967v1 Announce Type: cross Abstract: Despite the remarkable synthesis capabilities of text-to-image (T2I) models, safeguarding them against content violations remains a persistent challen