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Newest papers, page 49
$Δτ$-Bench: Pushing Agents Toward a Moving Capability
In this paper, we introduce $Δτ$-Bench, an executable agent benchmark that models the structural evolution of large tool ecosystems.A Russian, a Brazilian, and a German Walk into a Bar, Ask the Same Question-- And Get Three Different Answers: Profiling LLM Perspective Diversity on Contested Topics
Large Language Models(LLMs) have shown strong performance on tasks with verifiable answers, but many real-world queries involve subjectivity, disagreement, and conflicting evidence.Transformer to GPT-5: Advancements, Limitations, and Future Directions in Large Language Model Design
Large Language Models (LLMs) have revolutionized Artificial Intelligence (AI) by their extraordinary capabilities, like contextual understanding, few-shot/zero-shot learning, code generation…Factual Yet One-Sided: Stance Poisoning and Evidence Balancing in Retrieval-Augmented Generation
The stance expressed in responses from retrieval-augmented generation systems is significantly influenced by the stance distribution of the retrieved materials.Automated, auditable dating of the Babylonian Astronomical Diaries with language models and astronomical tools
The Babylonian Astronomical Diaries record the sky over nearly six centuries.Birth, Death and Diff: Insertion-Based Sequence Generation with Corrections
Insertion-based masked diffusion models enable flexible-length, parallel generation by interleaving mask insertion with token unmasking.CoLink: Global Compression and Knowledge Linking for Multi-Turn Dialogue Modeling
Extracting salient information from long-horizon dialogue histories remains a significant challenge for Large Language Models (LLMs) due to the restricted context windows and efficient retrieval…Improving the Chain-of-Thought Compressibility of Pruned Reasoning Models via Long--Short Contrastive Pruning
Large reasoning models are costly to serve because they are large and because they generate long chains of thought (CoT).Xing USP: A Cross-Family Semantic Contract for Information Extraction and Intent-Slot Parsing
Structured semantic parsing is typically judged by whether the correct category is assigned, which leaves value recovery and instance-level associations unexamined: a system may recognize an event…Beyond the Opening: Tracing the First Token's Persistent Influence on Reasoning Length
Understanding how individual token choices affect reasoning length is important for characterizing reasoning models.Whether or Where? Tail Calibration Signals Finite-Budget Reward Hacking in Best-of-N Selection
Best-of-N (BoN) inference returns the candidate with the highest proxy reward, so a larger $N$ tests the proxy's extreme tail more than its average ranking quality.AndroidFlux: Evaluating and Reward Modeling Failure Recovery Capabilities in Mobile Use Multimodal Agents
Mobile-use multimodal agents are typically evaluated by task success from a clean initial state, which does not isolate their ability to recover from intermediate errors.A Domain-Aware Pipeline for Structured Extraction and Retrieval-Augmented Question Answering over arXiv Superconductivity Literature
Scientific literature in materials physics is growing faster than researchers can manually inspect it, yet most retrieval tools rely on keyword matching or generic question answering that ignores…Toward Neuroadaptive Communication Interfaces: A Framework for Personalized Speech and Language Support
Speech and language technologies have expanded access to communication, but the support they provide is often fixed.Efficient Proof Generation for Lean Statements with Multiple Candidate Answers
In formal systems such as Lean 4, efficiently finding answers to mathematical problems and generating verifiable proofs is an important task in automated mathematical reasoning.What Effort Level Should I Choose? On the Economics of Reasoning Effort in LLM Agents
Generative models increasingly expose a reasoning effort setting that lets users scale inference-time compute, trading higher cost for potentially improved performance.Wave Is All You Need: A Quantum Language Model Based on Fully Connected Quantum Boltzmann Machine
This work proposes a self-attention mechanism based on the fully connected quantum Boltzmann machine (FC-QBM), and further constructs a fully connected quantum Boltzmann machine language model…Does the Voynich Manuscript Mean Anything? Calibrated Tests Find Little Trace of Language
The Voynich manuscript is a fifteenth-century book in a script that no one can read.The Price of Scale in Proactive Memory Recall
A long-lived assistant that brings up memories without being asked must decide at every turn whether anything in its store is worth an interruption.STEP: Soft Trajectory Estimation of Prediction Correctness via Per-Step Probability Scoring
Estimating the correctness of large language model (LLM) predictions without access to ground truth is critical for reliable deployment in high-stakes settings.