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Reproducing, Analyzing, and Detecting Reward Hacking in Rubric-Based Reinforcement Learning
Announce Type: new Abstract: Rubric-based reinforcement learning (RL) uses an LLM-as-a-Judge (LaaJ) to score model outputs according to rubrics as rewards. However, policy models may exploit latent biases in the judge, leading to reward hacking and ineffective or unsafe training outcomes. In real-world rubric-based RL, such hacking behaviors are often subtle and entangled with multiple judge biases, making them difficult to analyze, detect, and mitigate.
In a first, scientists translated an entire viral genome so a quantum computer could read and analyze it
In a first, scientists translated an entire viral genome so a quantum computer could read and analyze it Scientists have uploaded a viral genome to a quantum computer, marking an important step for the future of quantum-enabled advancements in biology. Scientists say they have uploaded a real genome to a quantum computer for the first time, marking an important step in applying the emerging technology to biology. The researchers encoded the entire genome of the hepatitis D virus (HDV) onto a...
Pseudo-Equilibria, or: How to Stop Worrying About Crypto and Just Analyze the Game
Announce Type: replace Abstract: We consider the problem of a game theorist analyzing a game that uses cryptographic protocols. Ideally, a theorist abstracts protocols as ideal, implementation-independent primitives, letting conclusions in the "ideal world" carry over to the "real world." This is crucial, since the game theorist cannot--and should not be expected to--handle full cryptographic complexity.
Analyzing the Evolution of Structural Communities within Microservice Architecture
arXiv:2606.04047v1 Announce Type: new Abstract: In recent years, the detection of anti-patterns in microservice architecture has gained traction, particularly to identify instances of Microservice Architectural Degradation. In such tasks, the microservice architecture is often modeled as a network of microservice dependencies. Recent works have explored how to assess the evolution of such architectural networks by considering the architecture of consecutive releases of the project.
Analyzing Visual Attention Patterns During Band Rehearsal with Mobile Eye Tracking
Announce Type: new Abstract: Visual attention is central to ensemble coordination, yet how musicians allocate gaze during naturalistic rehearsal remains poorly understood. We present a pilot study using mobile eye tracking to examine gaze behaviour in a four-member band across three songs, each practiced twice. Musicians wore Pupil Labs Neon eye trackers, and YOLOv8-assisted scene annotations mapped fixations to ensemble members and objects in view.
Analyzing the dynamics in defense/counter-defense games among hosts and pathogens
In the dynamic interplay between hosts and pathogens, hosts may produce a defense compound that acts as a toxin to deter pathogen attack. Conversely, pathogens may evolve to produce a counter-defense enzyme, neutralizing the host's toxin. This evolutionary arms race incurs costs for both parties, prompting adaptations and strategic shifts.
VET: A Framework for Analyzing AI Discourse
arXiv:2606.01929v1 Announce Type: new Abstract: Public discourse on AI has become polarized; exaggerated positions on AI in traditional and social media threaten the development of AI Literacy among the general public. In this article, I introduce the VET Framework, a method for categorizing AI discourse along the dimensions of valence, effectiveness, and trajectory. I show how this framework can be used to identify, compare, and critique prevalent narratives of AI Hype, AI Doom, AI Denial,...
BIAS-ID: A Framework for Analyzing Transformation Biases in AI-Generated Image Detectors
arXiv:2605.31153v1 Announce Type: new Abstract: Given the surge of harmful AI-generated imagery online, reliably distinguishing authentic images from generated ones has become an urgent research topic. While many proposed detection methods perform well under controlled settings, they often collapse when tested on real-world data.
Rerank Before You Reason: Analyzing Reranking Tradeoffs through Effective Token Cost in Deep Search Agents
arXiv:2601.14224v2 Announce Type: replace Abstract: Deep research agents rely on iterative retrieval and reasoning to answer complex queries, but scaling test-time computation raises significant efficiency concerns. We study how to allocate reasoning budget in deep search pipelines, focusing on the role of listwise reranking.
Kornacki Cam: Watch Steve analyze midterm primary election results
Steve Kornacki tracks the race for Los Angeles mayor 03:24 NBA star Steph Curry signs apparel deal with Chinese company Li-Ning 04:17 School bus in St. Paul, MN crashes into university building 01:01 New Jersey police ramp up security as state prepares for World Cup final 04:28 Graduation surprise from doctor of teen who battled stage four cancer 01:21 Passengers restrain man accused of trying to enter cockpit mid-flight 01:30 Trump to speak at rescheduled White House Correspondents' Dinner...