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,...
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...
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...
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...
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...
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...
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts - ACL Anthology
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing - ACL Anthology
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations - ACL Anthology
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations - ACL Anthology
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts - ACL Anthology
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) - ACL Anthology
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track - ACL Anthology
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track - ACL Anthology
Law in Non-Places: A Comment on Siva Thambisetty, ‘The Unfree Commons: Freedom of Marine Scientific Research and the Status of Genetic Resources beyond National Jurisdiction’ (2025) 88(2) MLR 300
There Can Be Only Two (Verdicts): The Presumption of Innocence and Jury Verdicts in Criminal Trials
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...
The Ocean Treaty’s Novel Approach to Genetic Resources: A Response to Brad Sherman’s ‘Law in Non-Places’
Michigan antitrust lawsuit says oil companies hobbled EVs and renewables
The energy industry is pressing for laws that would ban climate liability lawsuits.
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.
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.
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...
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...
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...
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...
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...