For every paper on this page, at least one of the original authors has seen our plain-language explanation and engaged with it — either confirming it reads accurately or requesting corrections that we then applied. An endorsement does not mean the authors formally approve every sentence, but it does mean the explanation has passed the eyes of the people who wrote the paper.

1336 papers reviewed by authors · 341–350 / 1336

💬 NLP

Novel Claim or Déjà Vu? Rethinking "Contamination-Free'' Dynamic Evaluation for Multimodal Automated Fact-Checking

This paper challenges the assumption that dynamic benchmarks are inherently contamination-free by demonstrating that a significant portion of post-cut-off claims remain verifiable via pre-existing knowledge, which can artificially inflate multimodal fact-checking performance and distort system rankings, thereby necessitating stricter evaluation protocols.

Haorui He, Xinwen Chen, Dacheng Wen, Reynold Cheng, Francis C. M. Lau, Yupeng Li2026-07-28✓ Author reviewed ⓘ
⚛️ phenomenology

Baryogenesis from the Thermodynamic Arrow of Time: a Transfer-Function Bound and an Entropy-Clock Mechanism

This paper proposes a baryogenesis mechanism driven by an "entropy-clock" chemical potential during reheating, establishing a transfer-function bound that demonstrates successful freeze-out requires the entropy production timescale to overlap with the charge-violation scale, thereby constraining the reheating temperature to be comparable to the freeze-out temperature.

Yakov Mandel2026-07-28✓ Author reviewed ⓘ
💬 NLP

Language-Routed RAG and Direct Option Scoring for Multilingual Financial QA: DS@GT at FinMMEval

The DS@GT team proposes a language-routed, retrieval-augmented pipeline for multilingual financial QA that combines BGE-M3 embeddings with weighted Reciprocal Rank Fusion and direct option scoring via next-token log-probabilities, demonstrating that optimal performance requires language-specific model selection and careful avoidance of chain-of-thought prompting for certain languages.

Justice Ayela, Kabir Sahni2026-07-28✓ Author reviewed ⓘ
🔭 astrophysics

Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method

This paper demonstrates that optimizing the Dark Energy Survey's Self-Organizing Map photometric redshift method by tailoring the algorithm for redshift estimation and incorporating g-band flux information significantly improves redshift distribution characterization, reducing bin overlap by up to 66% and establishing a robust framework for future DES Year 6 and stage IV surveys.

A. Campos, B. Yin, S. Dodelson, A. Amon, A. Alarcon, C. Sánchez, G. M. Bernstein, G. Giannini, J. Myles, S. Samuroff, O. (…)2026-07-28✓ Author reviewed ⓘ
🔭 astrophysics

Reconstructing PTA measurements via early seeding of supermassive black holes

This paper investigates how early seeding mechanisms for supermassive black holes, specifically comparing direct collapse black holes and Dark Star collapse, influence the nanohertz gravitational wave background detected by pulsar timing arrays, finding that Dark Star seeds with a specific number density could dominate the signal while offering a pathway to constrain seed populations.

Sohan Ghodla, Cosmin Ilie2026-07-28✓ Author reviewed ⓘ
🤖 machine learning

Adaptive Data Admission and Retention for Streaming Federated Learning

This paper proposes an Active-Constraint Drift-Plus-Penalty (ACDPP) framework for streaming federated learning with limited client memory, which jointly optimizes server-side data admission and client-side retention to minimize cumulative excess population risk while satisfying sampling-cost and buffer constraints, achieving sublinear regret guarantees validated by experiments.

Zhuoyi Zhao, Ben Liang2026-07-28✓ Author reviewed ⓘ
💬 NLP

Gubernaut: A Deterministic Homeostatic Controller for Affect-Regulated LLM Agents, Validated Across Independent Model Families

This paper introduces Gubernaut, a deterministic, model-agnostic runtime controller that uses a token-free meta-level monitoring affect telemetry to successfully regulate reactive failure modes in large language model agents across multiple frontier model families, as validated by a rigorous, pre-registered evaluation protocol.

Dushyant Sharma2026-07-28✓ Author reviewed ⓘ
📄 health informatics

Digital Health Adoption, eHealth Literacy, and Trust in AI Among Generation Z University Students in Sri Lanka: An Empirical Study

This study reveals that while Generation Z university students in Sri Lanka possess high eHealth literacy and increasingly rely on AI for health information, their adoption of digital health services remains constrained by significant privacy concerns and a persistent preference for traditional face-to-face consultations.

Athukorala, S. C.2026-07-28✓ Author reviewed ⓘ