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EpiFormer: Learning Antigen-Antibody Interactions for Epitope Prediction via Geometric Deep Learning

arXiv:2606.04154v1 Announce Type: cross Abstract: Antibodies neutralize foreign antigens by binding to specific surface regions called epitopes. Computational epitope prediction is critical for unders

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Episodic Memory Temporal Consistency for Cooperative Multi-Agent Reinforcement Learning

DGX agent

arXiv:2606.04492v1 Announce Type: new Abstract: Cooperative Multi-Agent Reinforcement Learning (MARL) frequently suffers from severe reward sparsity and exploration bottlenecks. While episodic memory

agentsarxiv-cs-lg

4 Jun 2026

EvalStop: Using World Feedback to Detect and Correct Reward Overoptimization in Multi-Tenant RLHF Platforms

arXiv:2606.04145v1 Announce Type: cross Abstract: Cloud LLM fine-tuning platforms increasingly serve RLHF workloads, where a learned reward model is optimized as a proxy for human quality. As Gao et a

Evaluating Autoformalization Robustness via Semantically Similar Paraphrasing

arXiv:2511.12784v3 Announce Type: replace Abstract: Large Language Models (LLMs) have recently emerged as powerful tools for autoformalization. Despite their impressive performance, these models can s

researcharxiv-cs-cl

Evaluating Large Language Models in Dynamic Clinical Decision-Making with Standardized Patient Cases

model-releasesarxiv-cs-cl

arXiv:2606.05112v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed as clinical agents, yet static, single-turn benchmarks cannot capture how a model dynamically del

Evaluating Reasoning Fidelity in Visual Text Generation

arXiv:2606.04479v1 Announce Type: cross Abstract: Recent text-to-image (T2I) models can render highly legible and well-structured text within images, enabling applications including document generatio

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction

arXiv:2602.23312v3 Announce Type: replace-cross Abstract: Leader-follower interaction is an important paradigm in human-robot interaction (HRI). Yet, assigning roles in real time remains challenging f

EvoPrompt: Guided Prompt Evolution for Vision-Language Models Adaptation

arXiv:2603.09493v2 Announce Type: replace-cross Abstract: The adaptation of large-scale vision-language models (VLMs) to downstream tasks with limited labeled data remains a significant challenge. Whi

Exact Unlearning in Reinforcement Learning

arXiv:2606.04182v1 Announce Type: cross Abstract: We formulate the problem of exact unlearning in reinforcement learning, where the goal is to design an efficient framework that enables the removal of

Expectations vs. Realities: The Cost of MSE-Optimal Forecasting Under Conditional Uncertainty

arXiv:2606.04342v1 Announce Type: cross Abstract: Multi-step time series forecasting (MSF) is commonly evaluated using point-wise error metrics such as mean squared error (MSE), implicitly treating th

applicationsarxiv-cs-ai

Expert-Aware Refusal Steering

arXiv:2606.04160v1 Announce Type: new Abstract: Safety alignment in instruction-tuned large language models (LLMs) depends on a model's ability to reliably refuse to respond to harmful or disallowed r

safetyarxiv-cs-cl

Explainably Safe Reinforcement Learning

arXiv:2606.04634v1 Announce Type: new Abstract: Trust in a decision-making system requires both safety guarantees and the ability to interpret and understand its behavior. This is particularly importa

safetyarxiv-cs-lg

Explaining a probabilistic prediction on the simplex with Shapley compositions

arXiv:2408.01382v3 Announce Type: replace Abstract: Originating in game theory, Shapley values are widely used for explaining a machine learning model's prediction by quantifying the contribution of e

Agents

Exploring Cross-Scenario Generality of Agentic Memory Systems: Diagnostics and a Strong Baseline

arXiv:2606.04315v1 Announce Type: new Abstract: LLM agents accumulate histories that outgrow their context windows, motivating a growing literature on memory systems. Yet most existing designs are tun

agentsarxiv-cs-ai

Exploring the Topology and Memory of Consensus: How LLM Agents Agree, Fragment, or Settle When Forming Conventions

model-releasesarxiv-cs-cl

arXiv:2606.04197v1 Announce Type: cross Abstract: How much should an LLM agent remember, and how should multi-agent systems be connected when trying to reach consensus? We show these two design choice

Exposing Blindspots: Cultural Bias Evaluation in Generative Image Models

model-releasesarxiv-cs-cv

arXiv:2510.20042v3 Announce Type: replace Abstract: Generative image models produce striking visuals yet often misrepresent culture. Prior work has examined cultural bias mainly in text-to-image (T2I)

Extending Fair Null-Space Projections for Continuous Attributes to Kernel Methods

arXiv:2511.03304v2 Announce Type: replace-cross Abstract: With the on-going integration of machine learning systems into the everyday social life of millions the notion of fairness becomes an ever inc

Failed Reasoning Traces Tell You What Is Fixable (But Not by Reading Them)

arXiv:2606.05145v1 Announce Type: cross Abstract: When post-trained language models fail on reasoning problems, the common test-time-scaling response is to spend more compute on additional attempts, a

Agents

FALSIFYBENCH: Evaluating Inductive Reasoning in LLMs with Rule Discovery Games

arXiv:2606.04751v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents in scientific tasks. Yet whether these systems can effectively engage in for

agentsarxiv-cs-ai

Fast Cubical Persistent Homology on 2D and 3D Images via Union-Find, Pruning, and Lookup Tables

arXiv:2606.04801v1 Announce Type: new Abstract: We present Flash Cubical, a highly efficient computation of cubical persistence on a V-filtration for 2D and 3D images over F_2. The implementation is b

researcharxiv-cs-cv

Fast & Faithful Function Vectors

arXiv:2606.05079v1 Announce Type: new Abstract: Function vectors (FVs) are task representations elicited during in-context learning that can be used to steer Large Language Models (LLMs). However, des

researcharxiv-cs-cl

Federated Learning for Multi-Center Sepsis Early Prediction with Privacy-Preserving

arXiv:2606.04338v1 Announce Type: new Abstract: Privacy-sensitive and distributed characteristics of multi-center medical data bring severe obstacles to centralized modeling for accurate early predict

applicationsarxiv-cs-lg

Few Tokens, Big Leverage: Preserving Safety Alignment by Constraining Safety Tokens during Fine-tuning

arXiv:2603.07445v2 Announce Type: replace Abstract: Large language models (LLMs) often require fine-tuning (FT) to perform well on downstream tasks, but FT can induce safety-alignment drift even when

safetyarxiv-cs-cl

FindIt: A Format-Informed Visual Detection Benchmark for Generalist Multimodal LLMs

model-releasesarxiv-cs-cv

arXiv:2606.04282v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are predominantly evaluated on free-form vision-language tasks such as visual question answering, captioning, a

Fine-grained Fragment Retrieval in Multi-modal Long-form Dialogues

arXiv:2606.04591v1 Announce Type: new Abstract: With the widespread adoption of multi-modal communication platforms, long-form dialogues interleaving text and images have become increasingly common. U

applicationsarxiv-cs-cl

Finite-Iteration Local Dynamics and Warm Starts for Alternating Power Iteration in Spiked Tensor PCA

arXiv:2606.04065v1 Announce Type: cross Abstract: We study simultaneous alternating power iteration for fixed-order asymmetric rank-one spiked tensor models. Our main contribution is a finite-iteratio

FinTradeBench: A Financial Reasoning Benchmark for LLMs

arXiv:2603.19225v3 Announce Type: replace-cross Abstract: Real-world financial decision-making is a challenging problem that requires reasoning over heterogeneous signals, including company fundamenta

Hardware

Fitting scattered data with optional monotonicity constraints on GPU: LipFit package

arXiv:2606.04670v1 Announce Type: cross Abstract: This paper presents a method of multivariate scattered data interpolation and approximation that produces optimal Lipschitz-continuous approximation,

hardwarearxiv-cs-lg

Fixed Aggregation Features Can Rival GNNs

arXiv:2601.19449v2 Announce Type: replace Abstract: Graph neural networks (GNNs) are widely believed to excel at node representation learning through trainable neighborhood aggregations. We challenge

applicationsarxiv-cs-lg

FLAGG: Flexible Autoregressive Graph Generation

arXiv:2606.05067v1 Announce Type: new Abstract: The Deep Graph Generation's panorama spans two extremes: one-shot and sequential models. The former generates nodes and edges jointly, while the latter

safetyarxiv-cs-lg

Flatness and Generalization: Learning Multi-Index Models with Homogeneous Neural Networks

arXiv:2606.04429v1 Announce Type: cross Abstract: A common heuristic used to explain the generalization of first-order gradient methods on non-convex neural networks is that 'flat interpolators genera

Flow Matching Calibration for Simulation-Based Inference under Model Misspecification

model-releasesarxiv-cs-lg

arXiv:2509.23385v5 Announce Type: replace-cross Abstract: Simulation-based inference (SBI) is transforming experimental sciences by enabling parameter estimation in complex non-linear models from simu

FoeGlass: Simple In-Context Learning Is Enough for Red Teaming Audio Deepfake Detectors

arXiv:2606.05101v1 Announce Type: cross Abstract: Audio deepfake detection (ADD) models are critical for countering the malicious use of text-to-speech (TTS) models. Evaluating and strengthening ADD m

Fog of Love: Engineering Virtuous Agent Behavior with Affinity-based Reinforcement Learning in a Game Environment

arXiv:2606.04750v1 Announce Type: new Abstract: Instilling virtuous behavior in artificial intelligence has seen increasing interest. One of the techniques proposed is known as affinity-based reinforc

Folded Transport MCMC: Certifiable Quotient Posterior Computation for Symmetric Bayesian Models

arXiv:2606.04307v1 Announce Type: new Abstract: Bayesian models with finite symmetry - mixture models with exchangeable components, structural identification with closely-spaced modes - define posteri

Food-R1: A Unified Multi-Task Food Vision-Language Model with Reinforcement Learning

model-releasesarxiv-cs-cv

arXiv:2606.04986v1 Announce Type: new Abstract: Recent studies have explored Vision-Language Models (VLMs) for food analysis. However, most existing methods rely primarily on supervised fine-tuning (S

Formal Semantics for Agentic Tool Protocols: A Process Calculus Approach

arXiv:2603.24747v2 Announce Type: replace Abstract: The emergence of large language model agents capable of invoking external tools has created urgent need for formal verification of agent protocols.

From Agent Traces to Trust: Evidence Tracing and Execution Provenance in LLM Agents

arXiv:2606.04990v1 Announce Type: cross Abstract: Large language model (LLM)-based agents increasingly solve complex tasks by interacting with external tools, retrieval systems, memory modules, enviro

From Live to Recording: Consumer Demand and Response to Price Across the Livestreaming Lifecycle

arXiv:2107.01629v3 Announce Type: replace-cross Abstract: Livestreaming has evolved into a thriving industry where creators can directly monetize and engage with their audiences and followers. In prac

From Motion Signals to Insights: A Unified Framework for Student Behavior Analysis and Feedback in Physical Education Classes

arXiv:2503.06525v2 Announce Type: replace-cross Abstract: Analyzing student behavior in educational scenarios is crucial for enhancing teaching quality and student engagement. Existing AI-based models

applicationsarxiv-cs-ai

Agents

From Prompt to Process: a Process Taxonomy and Comparative Assessment of Frameworks Supporting AI Software Development Agents

arXiv:2606.04967v1 Announce Type: cross Abstract: AI tools for programming are no longer just autocomplete or chat assistants: they organize themselves as development frameworks, with process, roles,

agentsarxiv-cs-ai

From Symbolic to Geometric: Enabling Spatial Reasoning in Large Language Models

arXiv:2606.04381v1 Announce Type: cross Abstract: Recent large language models (LLMs) often appear to exhibit spatial reasoning ability; however, this capability is largely symbolic, arising from patt

From Ticks to Flows: Dynamics of Neural Reinforcement Learning in Continuous Environments

arXiv:2606.04275v1 Announce Type: cross Abstract: We present a novel theoretical framework for deep reinforcement learning (RL) in continuous environments by modeling the problem as a continuous-time

From Untrusted Input to Trusted Memory: A Systematic Study of Memory Poisoning Attacks in LLM Agents

arXiv:2606.04329v1 Announce Type: cross Abstract: Memory is a core component of AI agents, enabling them to accumulate knowledge across interactions and improve performance. However, persistent memory

GARL: Game-Theoretic Reinforcement Learning for Multi-Agent Strategic Prioritisation

arXiv:2606.05002v1 Announce Type: new Abstract: LLM-based multi-agent systems are increasingly used for strategic decision-making tasks. In such settings, performance depends not only on individual mo

safetyarxiv-cs-cl

GeM-NR: Geometry-Aware Multi-View Editing for Nonrigid Scene Changes

arXiv:2606.05142v1 Announce Type: cross Abstract: Recent developments in multi-view image editing with generative models have brought us a step closer toward general 3D content generation and customiz

GENEB: Why Genomic Models Are Hard to Compare

model-releasesarxiv-cs-cl

arXiv:2606.04525v1 Announce Type: new Abstract: Progress in genomic foundation models is difficult to assess due to fragmented benchmarks, incompatible evaluation protocols, and task-specific reportin

Generalizable Multi-Task Learning for Wireless Networks Using Prompt Decision Transformers

arXiv:2606.04328v1 Announce Type: cross Abstract: Future wireless networks demand rapid adaptation to highly heterogeneous environments and dynamic task configurations, necessitating a shift from conv