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Newest papers, page 201
AnthroDial: Benchmarking LLM Anthropomorphism in Autonomous Social Interaction
Large language models (LLMs) are increasingly deployed as social agents, yet credible human-like interaction requires more than fluent responses or persona consistency.Storage Is Not Strategy: State-Conditioned Support Control for LLM Unlearning
Many localized large language model (LLM) unlearning methods select a small parameter subset from a localization signal and keep it fixed during optimization.One Threshold Does Not Fit All Languages: Language-Conditional Deferral for Reliable and Efficient Low-Resource Text Classification
In the Global South, the lower-income countries of Africa, Asia, and Latin America where most of the world's languages are spoken, a deployed text classifier usually runs on ordinary CPUs, serves…It's Not What the Image Shows: Irrelevant Context Destabilises VLM Judges Without Informing Them
Vision-language models (VLMs) are increasingly used in place of human annotators, making it important that substitutability tests reflect the model rather than incidental evaluation conditions.Learning Beyond What You Sample: Off-Policy-Aware Cross-Model Trajectory Exchange for RLVR
Reinforcement Learning with Verifiable Rewards (RLVR) methods such as GRPO rely on successful self-generated trajectories, but finite rollout budgets can produce all-fail groups with no reward-based…Retrieval Capacity of Self-Attention Under Competition
How many tokens from its context does a language model actually use, and what determines that number?How Many Labels Does a Language Need? Annotation Budgets and Cross-Lingual Pooling for African-Language Text Classification
Every text classifier for an African language begins with a budgeting question: how many labelled examples are needed, and can labels from other African languages stand in for them?Zero-shot Dependency Parsing with Unsupervised Cross-Lingual Bootstrapping
Pre-trained language models (PLMs) with encoder-based architectures have shown impressive capabilities in zero-shot cross-lingual transfer for various language understanding tasks.It's All Training: A Fully Synthetic Single-Stage Recipe for LLMs
Current pre-training datasets are derived from web crawls, with all their issues, and were not designed to support mid- and post-training pipelines--for instance, they contain little explicit…The Unequal Influence of Bad Advice: Using Training Data Attribution to Modulate Emergent Misalignment
Fine-tuning large language models on narrow, misaligned tasks can undo their post-training alignment and induce novel misaligned behaviors -- a phenomenon known as \emph{emergent misalignment} (EM).Overcoming Scaling Limits in On-Policy Self-Distillation for LLM Reasoning
On-policy self-distillation (OPSD) trains a student to match a privileged teacher distribution along its own sampled trajectory.Time-Anchored Diffusion Language Models: Latent-Space Caching for Fast Generation
Recent work on anchored diffusion language models improves denoising by shaping an intermediate latent space with supervised important-token targets.Learning What to Remember: Long-horizon Counterfactual Memory Optimization
Persistent textual memory allows language models to carry information across long interactions, but learning what to remember is fundamentally a credit-assignment problem.SelfSearch: Reward-Free Search for Self-Improving Agents
Advances in the coding capabilities of LLM agents allow them to inspect and modify their own instructions, tools, and execution procedures.On Trajectory-Aware Training for Masked Diffusion Language Models
Masked diffusion models (MDMs) generate text by unmasking several tokens per step, but they are trained and sampled under different conditions.$S^3$: Spectral Null-Space Swap Makes Reasoning Models Efficient
LLMs trained with Chain-of-thought excel in reasoning capability, but often come with excessive token cost.BITEM at the NTCIR-19 R2C2 Task: Predicting Confidence from Agentic RAG Pipeline Signals
The BITEM team entered both subtasks of the NTCIR-19 R2C2 task with a single agentic pipeline, in which a model searches, reads and records evidence over a movie corpus while an orchestrator holds…Auditable Long-Term Memory: A Deterministic Retrieval Chain Measured at 479/475 of 500 on LongMemEval-S
We evaluate an auditable long-term memory system on LongMemEval-S.Dr. OPD: Learning What to Follow for Optimal On-Policy Distillation of Large Language Models
On-policy distillation (OPD) trains a student on its own generated responses using dense, token-level supervision from a stronger teacher.Gender bias across LLMs is common and highly heterogeneous
Understanding gender biases in large language models (LLMs) is increasingly important as these systems become embedded in decision-support tools with real consequences.