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LOW Academic International

DiffuRank: Effective Document Reranking with Diffusion Language Models

arXiv:2602.12528v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have inspired new paradigms for document reranking. While this paradigm better exploits the reasoning and contextual understanding capabilities of LLMs, most existing LLM-based rerankers rely on autoregressive generation,...

1 min 1 month, 1 week ago
standing
LOW Academic International

The Appeal and Reality of Recycling LoRAs with Adaptive Merging

arXiv:2602.12323v1 Announce Type: new Abstract: The widespread availability of fine-tuned LoRA modules for open pre-trained models has led to an interest in methods that can adaptively merge LoRAs to improve performance. These methods typically include some way of selecting LoRAs...

1 min 1 month, 1 week ago
appeal
LOW Academic International

Multi-Agent Model-Based Reinforcement Learning with Joint State-Action Learned Embeddings

arXiv:2602.12520v1 Announce Type: new Abstract: Learning to coordinate many agents in partially observable and highly dynamic environments requires both informative representations and data-efficient training. To address this challenge, we present a novel model-based multi-agent reinforcement learning framework that unifies joint...

1 min 1 month, 1 week ago
standing
LOW Academic International

AMPS: Adaptive Modality Preference Steering via Functional Entropy

arXiv:2602.12533v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) often exhibit significant modality preference, which is a tendency to favor one modality over another. Depending on the input, they may over-rely on linguistic priors relative to visual evidence, or...

1 min 1 month, 1 week ago
evidence
LOW Academic International

Exploring Accurate and Transparent Domain Adaptation in Predictive Healthcare via Concept-Grounded Orthogonal Inference

arXiv:2602.12542v1 Announce Type: new Abstract: Deep learning models for clinical event prediction on electronic health records (EHR) often suffer performance degradation when deployed under different data distributions. While domain adaptation (DA) methods can mitigate such shifts, its "black-box" nature prevents...

1 min 1 month, 1 week ago
evidence
LOW Academic International

Unifying Model-Free Efficiency and Model-Based Representations via Latent Dynamics

arXiv:2602.12643v1 Announce Type: new Abstract: We present Unified Latent Dynamics (ULD), a novel reinforcement learning algorithm that unifies the efficiency of model-free methods with the representational strengths of model-based approaches, without incurring planning overhead. By embedding state-action pairs into a...

1 min 1 month, 1 week ago
motion
LOW Journal International

Colleague Societies

1 min 1 month, 1 week ago
standing
LOW Journal International

International Legal Materials

2 min 1 month, 1 week ago
standing
LOW Journal International

Financial Support

2 min 1 month, 1 week ago
standing
LOW Journal International

MLR Forum

1 min 1 month, 1 week ago
jurisdiction
LOW Journal International

Conor Gearty

We are deeply saddened to announce that Conor Gearty, a long-standing member of the Modern Law Review Editorial Committee, died suddenly on 11 September 2025 at the age of 67. Conor was appointed to the Committee in 2009, taking on...

1 min 1 month, 1 week ago
standing
LOW News International

Michigan antitrust lawsuit says oil companies hobbled EVs and renewables

The energy industry is pressing for laws that would ban climate liability lawsuits.

1 min 1 month, 1 week ago
lawsuit
LOW News International

Hollywood isn’t happy about the new Seedance 2.0 video generator

Hollywood organizations are pushing back against a new AI video model called Seedance 2.0, which they say has quickly become a tool for “blatant” copyright infringement.

1 min 1 month, 1 week ago
motion
LOW News International

Airbnb plans to bake in AI features for search, discovery and support

Airbnb CEO Brian Chesky said the company wants to increase its use of large language models for customer discovery, support and engineering.

1 min 1 month, 1 week ago
discovery
LOW Academic International

NL2LOGIC: AST-Guided Translation of Natural Language into First-Order Logic with Large Language Models

arXiv:2602.13237v1 Announce Type: new Abstract: Automated reasoning is critical in domains such as law and governance, where verifying claims against facts in documents requires both accuracy and interpretability. Recent work adopts structured reasoning pipelines that translate natural language into first-order...

1 min 1 month, 1 week ago
standing
LOW Academic International

TemporalBench: A Benchmark for Evaluating LLM-Based Agents on Contextual and Event-Informed Time Series Tasks

arXiv:2602.13272v1 Announce Type: new Abstract: It is unclear whether strong forecasting performance reflects genuine temporal understanding or the ability to reason under contextual and event-driven conditions. We introduce TemporalBench, a multi-domain benchmark designed to evaluate temporal reasoning behavior under progressively...

1 min 1 month, 1 week ago
standing
LOW Academic International

Accuracy Standards for AI at Work vs. Personal Life: Evidence from an Online Survey

arXiv:2602.13283v1 Announce Type: new Abstract: We study how people trade off accuracy when using AI-powered tools in professional versus personal contexts for adoption purposes, the determinants of those trade-offs, and how users cope when AI/apps are unavailable. Because modern AI...

1 min 1 month, 1 week ago
evidence
LOW Academic International

DiffusionRollout: Uncertainty-Aware Rollout Planning in Long-Horizon PDE Solving

arXiv:2602.13616v1 Announce Type: new Abstract: We propose DiffusionRollout, a novel selective rollout planning strategy for autoregressive diffusion models, aimed at mitigating error accumulation in long-horizon predictions of physical systems governed by partial differential equations (PDEs). Building on the recently validated...

1 min 1 month, 1 week ago
evidence
LOW Academic International

Guided Collaboration in Heterogeneous LLM-Based Multi-Agent Systems via Entropy-Based Understanding Assessment and Experience Retrieval

arXiv:2602.13639v1 Announce Type: new Abstract: With recent breakthroughs in large language models (LLMs) for reasoning, planning, and complex task generation, artificial intelligence systems are transitioning from isolated single-agent architectures to multi-agent systems with collaborative intelligence. However, in heterogeneous multi-agent systems...

1 min 1 month, 1 week ago
standing
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Impact Distribution

Critical 0
High 0
Medium 11
Low 1377