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Beyond Binary Rewards: A Comparative Study of Reward Design for Reinforcement Unlearning

arXiv:2607.27968v1 Announce Type: new Abstract: Machine unlearning seeks to selectively remove specific knowledge from trained language models without full retraining, a growing necessity under privac

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Beyond Borrowed Histories: Person-Aligned User Simulation for Interactive Role-Playing Evaluation

DGX agent

arXiv:2607.27816v1 Announce Type: new Abstract: Role-playing agents (RPAs) have become one of the most important consumer applications of large language models. Users engage in multi-turn conversation

model-releasesarxiv-cs-cl

31 Jul 2026

Beyond Classification: Pathology Foundation Models as Detection Encoders for Mitotic Figures

arXiv:2607.28007v1 Announce Type: new Abstract: Pathology foundation models (FMs) are models trained on vast amounts of typically unlabeled data and have been shown to yield regularized latent spaces

Beyond Feeling Better: Capability-Sustaining Emotional Dialogue as a Longitudinal Research Paradigm

arXiv:2607.27851v1 Announce Type: new Abstract: Emotional dialogue research includes two influential strategy traditions. Empathetic dialogue prioritizes understanding a speaker's emotional experience

safetyarxiv-cs-cl

Beyond Frame Selection: Generative Latent Evidence Aggregation for Long-Video Understanding

arXiv:2607.28516v1 Announce Type: new Abstract: Long-video understanding commonly compresses videos into a small set of frames or visual tokens for answer generation. Existing compact pipelines focus

Beyond Geometric Complementarity: Coherent Overlap in Sparse Mixture-of-Experts Routing

arXiv:2607.28308v1 Announce Type: new Abstract: Sparse mixture-of-experts (MoE) language models route each token to multiple experts, suggesting a geometric account of their benefit: co-selected exper

Beyond KV Reconstruction: Functional Reconstruction for MLA Draft Models in Speculative Decoding

arXiv:2607.27269v1 Announce Type: new Abstract: Multi-head latent attention (MLA) is increasingly important for long-context LLM inference because compact latent states replace the growing key-value (

Beyond Sentiment: Structured Information Extraction from Financial News

arXiv:2607.28496v1 Announce Type: new Abstract: Financial sentiment analysis has become a standard component in news-driven stock prediction, yet it reduces rich, multi-dimensional news articles to a

Beyond Similarity: Grounded Agentic Extraction and Expert-Adjudicated Evaluation of Intertextuality in Classical Chinese Histories

arXiv:2607.27595v1 Announce Type: new Abstract: Computational approaches to intertextuality have advanced from string matching to neural retrieval, yet their outputs, similarity scores and parallel-pa

Beyond the Best Teacher: Expanding and Compressing the Reasoning Solution Manifold

arXiv:2607.27770v1 Announce Type: new Abstract: A single reinforcement-learning run can produce a strong reasoner yet an incomplete teacher: it often amplifies only a subset of the valid solution mode

local-aiarxiv-cs-lg

Beyond the Bidirectional Promise: Re-evaluating the Robustness of Diffusion Language Models

arXiv:2607.27386v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) offer a compelling alternative to autoregressive (AR) generation by enabling bidirectional context and iterative refi

Beyond Visual Ambiguity: Guiding Robust Monocular Depth Estimation in Challenging Scenarios via Detailed Long Captions

arXiv:2607.28285v1 Announce Type: new Abstract: Monocular depth estimation (MDE) faces challenges with non-Lambertian surfaces and adverse weather conditions due to the visual ambiguities inherent in

BioPro: Towards Difference-Aware Gender Fairness for Vision-Language Models

arXiv:2512.00807v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) inherit significant social biases from their training data, notably in gender representation. Current fairness interve

safetyarxiv-cs-ai

BladeYOLO: Wind Turbine Blade Defect Detection with Limited Annotations and Weak-Saliency Awareness

arXiv:2607.28065v1 Announce Type: new Abstract: Wind turbine blade defect detection remains highly challenging in real-world inspection scenarios due to limited on-site data and the subtle visual char

applicationsarxiv-cs-cv

BlindPSNR: A No-Reference Fidelity Predictor for Low-Light Image Enhancement

arXiv:2607.27628v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) methods involve tunable parameters that are typically fixed, often leading to performance degradation when applied ac

Borrowed Strength: Best-of-N Search over a Code EncodingBreaks Self-Check Jailbreak Defenses

arXiv:2607.26639v1 Announce Type: cross Abstract: A self-check defense asks the target model to assess a request before answering it; SAGE, the strongest published instance, reports an average 99% def

safetyarxiv-cs-ai

BridgeAlign: Bridging Preference Alignment for Humanities and Social Sciences

arXiv:2607.27366v1 Announce Type: new Abstract: While data synthesis for large language models (LLMs) is prevalent, it primarily targets domains with verifiable answers, overlooking open-ended humanit

safetyarxiv-cs-cl

Bridging AI and Energy Forecasting: An Autonomous Workflow with Customized Toolkit

arXiv:2307.07191v3 Announce Type: replace Abstract: Energy forecasting is crucial for the power grid, but fundamentally different from general time series analysis: it highly relies on covariates like

Tutorials

Bridging the Gap in Ophthalmic AI: MM-Retinal-Reason Dataset and OphthaReason Model toward Dynamic Multimodal Reasoning

arXiv:2508.16129v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have recently demonstrated remarkable reasoning abilities with reinforcement learning paradigm. Although se

tutorialsarxiv-cs-ai

Building a User Foundation Model for the Open Web

arXiv:2607.28019v1 Announce Type: new Abstract: User foundation models have demonstrated strong results in e-commerce and social recommendation, but most industrial deployments assume environments whe

applicationsarxiv-cs-lg

Bunraku: Turning a Single Illustration into an Editable Live2D Character

arXiv:2607.27348v1 Announce Type: new Abstract: Live2D is the dominant 2D character-animation format for anime characters and virtual avatars, representing each character as a stack of RGBA layers dri

CACHE-UK: A Stability-Aware Memory Editor for Sequentially Updated Quantized LLMs in Finance

arXiv:2607.28292v1 Announce Type: new Abstract: Large Language Models (LLMs) deployed in dynamic financial environments face a critical challenge: maintaining factual accuracy as market conditions, re

applicationsarxiv-cs-cl

Calibrate Before Reason: Robust Visual Token Reduction against Semantic Drift in VLMs

arXiv:2607.27700v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) suffer from prohibitive inference overhead due to long sequences of visual tokens. However, existing visual token re

Calibrate Globally, Measure Everywhere: Scaling LLM-Based Prevalence Measurement Across A/B Experiments

arXiv:2602.16111v2 Announce Type: replace-cross Abstract: Online media platforms track the share of impressions associated with content attributes, or prevalence, to evaluate trade-offs and set guardr

applicationsarxiv-cs-ai

Agents

CaM-Wolf: Causal-Aware Multimodal Agents for Social Deduction Games

arXiv:2607.26393v1 Announce Type: new Abstract: Social deduction games (SDGs) such as Werewolf have become challenging testbeds for AI agents. These games require complex social skills such as reasoni

agentsarxiv-cs-ai

Can Agents Deceive? Evaluating Reasoning and Deception in ParliamentBench using a Social Deduction Game

arXiv:2607.28146v1 Announce Type: new Abstract: As large language models (LLMs) are deployed as agents in high-stakes settings, such as medical and legal systems, understanding their deceptive capabil

Tutorials

Can Large Language Models Execute Parent Orders?

arXiv:2607.28410v1 Announce Type: cross Abstract: Parent-order execution is a core problem in algorithmic trading, where the goal is to split a large order into smaller orders while reducing execution

tutorialsarxiv-cs-cl

Can LVLMs Uncover the Truth Behind Visual Illusions? An Analysis of Perceptual and Reasoning Capabilities

arXiv:2607.27747v1 Announce Type: new Abstract: Large Vision Language Models have integrated reasoning capabilities, elevating cognitive performance to new levels. However, existing evaluations either

Can Vision-Language Models Reason about AI Edits in Images?

arXiv:2607.28464v1 Announce Type: new Abstract: Detection and localization of AI-tampered images are critical for trustworthy AI, yet modern generative models have made such manipulations increasingly

local-aiarxiv-cs-cv

Capturing Token Tendencies for Training-Free Token Pruning in Multimodal Large Language Models

arXiv:2607.28341v1 Announce Type: new Abstract: While visual token pruning is essential for efficient Multimodal Large Language Models (MLLMs), existing training-free methods suffer from a critical li

local-aiarxiv-cs-cv

Causal Discovery with Inverted Self-attention for Multivariate Time Series

arXiv:2607.28212v1 Announce Type: new Abstract: Causal discovery in multivariate time series data is challenging due to complex interactions, high dimensionality, and nonlinear dependencies among vari

researcharxiv-cs-cl

Tutorials

CDAE: Enhancing Perturbation Robustness in Pretrained Language Models with Contrastive Denoising

arXiv:2607.28236v1 Announce Type: cross Abstract: Pre-trained language models have significantly improved sentence representation learning, yet their embedding remain sensitive to semantic preserving

tutorialsarxiv-cs-cl

Certifying when decision-time information justifies adaptive experimentation

arXiv:2607.27651v1 Announce Type: new Abstract: Adaptive laboratories choose measurements during experiments, yet most methods begin after adaptation is permitted. We introduce Opportunity-aware Polic

safetyarxiv-cs-lg

Challenges in annotations by humans and LLMs: A case study of evaluative language

arXiv:2607.28119v1 Announce Type: new Abstract: In this paper, we draw a comparison between linguists in training, a trained linguist, and annotations generated by large language models (LLMs) to find

applicationsarxiv-cs-cl

Agents

Change2Task: From Repository Changes to Executable Coding Agent Tasks and Environments

arXiv:2607.28591v1 Announce Type: cross Abstract: Scaling coding agents requires a continuing supply of executable data for training, benchmarking, and continuous evaluation. Each task must couple a r

agentsarxiv-cs-cl

Chem World: A Large-Scale Benchmark and Physics-Informed Framework for Trustworthy Chemical Property Prediction

arXiv:2607.28079v1 Announce Type: new Abstract: Chemical property prediction plays a critical role in accelerating scientific discovery in chemistry, materials science, and drug development. However,

Chimera: Designing and Chinchilla-Scaling Hybrid Visual Diffusion Transformers

arXiv:2607.28611v1 Announce Type: new Abstract: Visual generation increasingly requires high-resolution images, long videos, and multimodal context, making the quadratic cost of full attention prohibi

ChronoMem: Version Control and Semantic Rollback for Large Language Model Agent Memory

arXiv:2607.27773v1 Announce Type: new Abstract: LLM agents increasingly rely on long-term memory to support multi-session interaction and personalization. However, existing agent memory systems are de

CLAM: Continuous Latent Action Models for Robot Learning from Unlabeled Demonstrations

arXiv:2505.04999v2 Announce Type: replace-cross Abstract: Learning robot control policies from demonstrations typically requires action-labeled expert data, which is expensive to collect through teleo

applicationsarxiv-cs-lg

Class-Aware Reinforcement Learning for Counterfactual Explanation Generation

arXiv:2607.27905v1 Announce Type: new Abstract: Counterfactual explanations (CFEs) enhance the interpretability of black-box models by generating alternative instances with adjusted feature values tha

safetyarxiv-cs-lg

ClawTrack: Towards Trace-Level Evaluation and Improvement of Real-World Autonomous Agents

arXiv:2607.28037v1 Announce Type: new Abstract: As LLM-based agents are deployed in complex, multi-step workflows, a critical evaluation gap has emerged: most existing benchmarks judge only final outc

ClinLens: Towards Long-Horizon Coding Agents for Longitudinal Multimodal Clinical Data Science

model-releasesarxiv-cs-ai

arXiv:2607.26155v1 Announce Type: new Abstract: Clinical data-science agents must transform heterogeneous longitudinal records into auditable analyses, yet existing benchmarks largely isolate medical

CLIP-Guided Backdoor Defense through Entropy-Based Poisoned Dataset Separation

arXiv:2507.05113v3 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) are susceptible to backdoor attacks, where adversaries poison training data to implant backdoor into the victim mo

applicationsarxiv-cs-lg

Closed-Loop Bayesian Bandit Encoder with GRAND Receiver for a Bursty Interference Channel

arXiv:2607.15404v2 Announce Type: replace-cross Abstract: Interleaving mitigates burst errors but introduces decoding delay and removes temporal error structure that a channel-aware decoder could expl

researcharxiv-cs-lg

Cocktail-Talker: Multi-Speaker Dialog Modeling in Noisy Social Environments with Turn Action GRPO

arXiv:2607.27756v1 Announce Type: cross Abstract: Spoken dialog systems are typically designed for clean, dyadic interactions in which a single user and an assistant take turns speaking. Real-world so

applicationsarxiv-cs-cl

Collaborative Feature Aggregation for Face Super-Resolution and Robust Re-Identification

arXiv:2607.28130v1 Announce Type: new Abstract: We propose a novel collaborative approach for face super-resolution (SR) and robust person re-identification from sequential or multi-view facial images

Collusion with Competitive Marginals: Price-Level Audits Are Blind by Construction

model-releasesarxiv-cs-ai

arXiv:2607.26385v1 Announce Type: cross Abstract: Empirical work on algorithmic collusion asks one question of the data: are prices supracompetitive? We show this can be answered 'no' by a conspiracy

Compact Task-Aligned Imitation Learning for Laboratory Automation

arXiv:2603.01110v2 Announce Type: replace Abstract: Robotic laboratory automation has traditionally relied on carefully engineered motion pipelines and task-specific hardware interfaces, resulting in

local-aiarxiv-cs-ro