Policies on Large Language Model Usage at ICLR 2026
AAAI 2026 Spring Symposium Series - AAAI
To Mix or To Merge: Toward Multi-Domain Reinforcement Learning for Large Language Models
arXiv:2602.12566v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) plays a key role in stimulating the explicit reasoning capability of Large Language Models (LLMs). We can achieve expert-level performance in some specific domains via RLVR, such as coding...
Information-theoretic analysis of world models in optimal reward maximizers
arXiv:2602.12963v1 Announce Type: new Abstract: An important question in the field of AI is the extent to which successful behaviour requires an internal representation of the world. In this work, we quantify the amount of information an optimal policy provides...
Consistency of Large Reasoning Models Under Multi-Turn Attacks
arXiv:2602.13093v2 Announce Type: new Abstract: Large reasoning models with reasoning capabilities achieve state-of-the-art performance on complex tasks, but their robustness under multi-turn adversarial pressure remains underexplored. We evaluate nine frontier reasoning models under adversarial attacks. Our findings reveal that reasoning...
Optimal Take-off under Fuzzy Clearances
arXiv:2602.13166v1 Announce Type: new Abstract: This paper presents a hybrid obstacle avoidance architecture that integrates Optimal Control under clearance with a Fuzzy Rule Based System (FRBS) to enable adaptive constraint handling for unmanned aircraft. Motivated by the limitations of classical...
Quantum walk inspired JPEG compression of images
arXiv:2602.12306v1 Announce Type: cross Abstract: This work proposes a quantum inspired adaptive quantization framework that enhances the classical JPEG compression by introducing a learned, optimized Qtable derived using a Quantum Walk Inspired Optimization (QWIO) search strategy. The optimizer searches a...
Perceptual Self-Reflection in Agentic Physics Simulation Code Generation
arXiv:2602.12311v1 Announce Type: cross Abstract: We present a multi-agent framework for generating physics simulation code from natural language descriptions, featuring a novel perceptual self-reflection mechanism for validation. The system employs four specialized agents: a natural language interpreter that converts user...
Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment
arXiv:2602.12384v2 Announce Type: cross Abstract: Understanding why gradient-based training in deep networks exhibits strong implicit bias remains challenging, in part because tractable singular-value dynamics are typically available only for balanced deep linear models. We propose an alternative route based on...
RankLLM: Weighted Ranking of LLMs by Quantifying Question Difficulty
arXiv:2602.12424v1 Announce Type: cross Abstract: Benchmarks establish a standardized evaluation framework to systematically assess the performance of large language models (LLMs), facilitating objective comparisons and driving advancements in the field. However, existing benchmarks fail to differentiate question difficulty, limiting their...
Unleashing Low-Bit Inference on Ascend NPUs: A Comprehensive Evaluation of HiFloat Formats
arXiv:2602.12635v1 Announce Type: new Abstract: As LLMs scale, low-bit floating-point formats like MXFP and NVFP4 offer new opportunities for precision and efficiency. In this work, we evaluate HiFloat (HiF8 and HiF4), a family of formats tailored for Ascend NPUs. Through...
BaziQA-Benchmark: Evaluating Symbolic and Temporally Compositional Reasoning in Large Language Models
arXiv:2602.12889v1 Announce Type: new Abstract: We present BaziQA-Benchmark, a standardized benchmark for evaluating symbolic and temporally compositional reasoning in large language models. The benchmark is derived from 200 professionally curated, multiple-choice problems from the Global Fortune-teller Competition (2021--2025), where each...
Can we trust AI to detect healthy multilingual English speakers among the cognitively impaired cohort in the UK? An investigation using real-world conversational speech
arXiv:2602.13047v1 Announce Type: new Abstract: Conversational speech often reveals early signs of cognitive decline, such as dementia and MCI. In the UK, one in four people belongs to an ethnic minority, and dementia prevalence is expected to rise most rapidly...
Semantic Chunking and the Entropy of Natural Language
arXiv:2602.13194v1 Announce Type: new Abstract: The entropy rate of printed English is famously estimated to be about one bit per character, a benchmark that modern large language models (LLMs) have only recently approached. This entropy rate implies that English contains...
Geometric separation and constructive universal approximation with two hidden layers
arXiv:2602.12482v1 Announce Type: new Abstract: We give a geometric construction of neural networks that separate disjoint compact subsets of $\Bbb R^n$, and use it to obtain a constructive universal approximation theorem. Specifically, we show that networks with two hidden layers...
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...
Block-Sample MAC-Bayes Generalization Bounds
arXiv:2602.12605v1 Announce Type: new Abstract: We present a family of novel block-sample MAC-Bayes bounds (mean approximately correct). While PAC-Bayes bounds (probably approximately correct) typically give bounds for the generalization error that hold with high probability, MAC-Bayes bounds have a similar...
SLA2: Sparse-Linear Attention with Learnable Routing and QAT
arXiv:2602.12675v1 Announce Type: new Abstract: Sparse-Linear Attention (SLA) combines sparse and linear attention to accelerate diffusion models and has shown strong performance in video generation. However, (i) SLA relies on a heuristic split that assigns computations to the sparse or...
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing - ACL Anthology
Blacks of the American Society of International Law
The future of SEC enforcement authority
Please note that SCOTUS Outside Opinions constitute the views of outside contributors and do not necessarily reflect the opinions of SCOTUSblog or its staff. In April, the Supreme Court will hear Sripetch […]The postThe future of SEC enforcement authorityappeared first...
Episode 38: Non-intervention— past, present and future - EJIL: The Podcast!